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ORIGINAL RESEARCH
published: 24 July 2017
doi: 10.3389/fphys.2017.00487
Frontiers in Physiology | www.frontiersin.org 1July 2017 | Volume 8 | Article 487
Edited by:
Zhaoping Li,
Ronald Reagan UCLA Medical Center,
United States
Reviewed by:
Andrew Patterson,
Pennsylvania State University,
United States
Benjamin Moeller,
University of California, Davis,
United States
*Correspondence:
Kun Lu
kunlu@unc.edu
Specialty section:
This article was submitted to
Gastrointestinal Sciences,
a section of the journal
Frontiers in Physiology
Received: 09 April 2017
Accepted: 26 June 2017
Published: 24 July 2017
Citation:
Bian X, Chi L, Gao B, Tu P, Ru H and
Lu K (2017) Gut Microbiome
Response to Sucralose and Its
Potential Role in Inducing Liver
Inflammation in Mice.
Front. Physiol. 8:487.
doi: 10.3389/fphys.2017.00487
Gut Microbiome Response to
Sucralose and Its Potential Role in
Inducing Liver Inflammation in Mice
Xiaoming Bian 1, Liang Chi 2, Bei Gao 1, Pengcheng Tu 2, Hongyu Ru 3and Kun Lu 2*
1Department of Environmental Health Science, University of Georgia, Athens, GA, United States, 2Department of
Environmental Sciences and Engineering, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States,
3Department of Population Health and Pathobiology, North Carolina State University, Raleigh, NC, United States
Sucralose is the most widely used artificial sweetener, and its health effects have been
highly debated over the years. In particular, previous studies have shown that sucralose
consumption can alter the gut microbiota. The gut microbiome plays a key role in
processes related to host health, such as food digestion and fermentation, immune cell
development, and enteric nervous system regulation. Inflammation is one of the most
common effects associated with gut microbiome dysbiosis, which has been linked to a
series of human diseases, such as diabetes and obesity. The aim of this study was to
investigate the structural and functional effects of sucralose on the gut microbiota and
associated inflammation in the host. In this study, C57BL/6 male mice received sucralose
in their drinking water for 6 months. The difference in gut microbiota composition
and metabolites between control and sucralose-treated mice was determined using
16S rRNA gene sequencing, functional gene enrichment analysis and metabolomics.
Inflammatory gene expression in tissues was analyzed by RT-PCR. Alterations in
bacterial genera showed that sucralose affects the gut microbiota and its developmental
dynamics. Enrichment of bacterial pro-inflammatory genes and disruption in fecal
metabolites suggest that 6-month sucralose consumption at the human acceptable daily
intake (ADI) may increase the risk of developing tissue inflammation by disrupting the gut
microbiota, which is supported by elevated pro-inflammatory gene expression in the liver
of sucralose-treated mice. Our results highlight the role of sucralose-gut microbiome
interaction in regulating host health-related processes, particularly chronic inflammation.
Keywords: artificial sweetener, sucralose, gut microbiota, metabolomics, inflammation
INTRODUCTION
Artificial sweeteners are commonly used food additives that have much higher sweetness intensities
than table sugars (Gardner et al., 2012). Consumption of artificial sweeteners is increasing in
the United States, and in 2008, the prevalence of consumption of beverages containing artificial
sweeteners was 24.1% among adults. Sucralose, which is 600 times sweeter than sucrose, is one of
the most commonly used artificial sweeteners in the market due to its extremely sugar-like taste,
lack of a bitter aftertaste, stability at high temperatures, and long shelf-life (Grice and Goldsmith,
2000; Sylvetsky et al., 2012). The health effects of sucralose have been highly debated over the years.
A number of previous studies concluded that sucralose is safe for its intended use as an artificial
Bian et al. Sucralose Alters the Gut Microbiome
sweetener and that the body acquires no calories from sucralose
(Grotz and Munro, 2009; Sylvetsky et al., 2012). Most ingested
sucralose is not absorbed or metabolized and moves through
the gastrointestinal tract unchanged (Roberts et al., 2000).
However, this does not prove that sucralose has no effect on
the gut microbiota. One study showed that a product containing
sucralose altered the rat gut microbiota and induce inflammatory
lymphocyte infiltration (Abou-Donia et al., 2008), but the study
was considered to be deficient in several aspects (Brusick et al.,
2009), including the use of high doses and a sucralose mixture
instead of pure sucralose. Another study that focused on the
metabolic effects of sucralose on environmental bacteria showed
that sucralose can inhibit the growth of certain bacterial species
(Omran et al., 2013). Therefore, sucralose may inhibit intestinal
bacteria and alter the gut microbiota, and these alterations could
affect host health.
The mucosal surfaces of the human intestines are host to more
than 100 trillion microbes (including bacteria, fungi, viruses, and
parasites) from more than 1,000 species (Ley et al., 2006; Qin
et al., 2010). Gut microbes interact with the host mucosa directly
via the recognition of pathogen-associated molecular patterns
(PAMPs), such as lipopolysaccharide, flagellin, and bacterial
DNA and RNA, by mucosal pattern recognition receptors (PRRs;
Maloy and Powrie, 2011). Alternatively, the interaction can
occur indirectly through secreted metabolites (Nicholson et al.,
2012). These interactions are involved in maintaining symbiotic
homeostasis. Increasing evidence indicates that this homeostasis
is vital for human health (Holmes et al., 2011; Tremaroli
and Backhed, 2012). Gut microbes can help maintain good
host health by participating in digestion and fermentation of
food, development of immune cells, regulation of the enteric
nervous system, and prevention of colonization by pathogens
(Holmes et al., 2011). The host, in turn, provides a habitat
and nutrients and secretes antibodies to inhibit the aggressive
expansion of microbes (Kamada et al., 2013). Being highly
diverse, the gut microbiota can be shaped by various factors,
including aging, diet, drugs, antibiotics, diseases, stress, exercise,
and environmental pollutants (Ley et al., 2006; Nicholson et al.,
2012), and if homeostasis is disrupted as a result of this shaping,
many adverse outcomes may occur, such as cardiovascular
disease, obesity, diabetes, allergies, and cancer (Ley et al., 2006).
For example, an increased ratio of Firmicutes to Bacteroidetes
was found in obese mice compared with their lean littermates
(Turnbaugh et al., 2006), and obesity-related phenotypes were
found to be transmissible in a study in which fecal microbes
from obese and lean human twins were transferred to germ-free
mice (Ridaura et al., 2013). Likewise, a remarkable increase in
taurocholic acid and Bilophila wadsworthia induced by dietary
fat promotes colitis in IL10-deficient mice (Devkota et al., 2012).
Metabolites produced from dietary choline by gut microbes
have been shown to be modulated in obesity, diabetes, and
cardiovascular diseases (Kim et al., 2010; Wang et al., 2011).
Abbreviations: PAMPs, pathogen-associated molecular patterns; PRRs, pattern
recognition receptors; IBD, inflammatory bowel disease; LPS, lipopolysaccharide;
iNOS, inducible nitric-oxide synthase; MMP-2, matrix metalloproteinase 2; ROS,
reactive oxygen species; GI, gastrointestinal.
Inflammation is one of the most common physical conditions
associated with gut microbiota dysbiosis. For example, acute
or chronic inflammation is the primary characteristic of
inflammatory bowel diseases (IBDs; Xavier and Podolsky, 2007),
of which a disrupted gut microbiota is one of the major
triggers in addition to genetic factors and the host immune
system, although the precise etiology remains unclear (Hill and
Artis, 2010). Moreover, increasing evidence demonstrates that
low-grade chronic inflammation induced by gut microbiota
disruption is associated with metabolic diseases (Holmes et al.,
2011). Obesity and diabetes are associated with low-grade
inflammation not only in adipose tissues but also systemically.
A study of bariatric surgery, a method of reducing body weight
for obese individuals, showed that one gut microbe species,
Faecalibacterium prausnitzii, is directly related to the reduction
of low-grade inflammation in obesity and diabetes (Furet et al.,
2010). Dyslipidemia induced by a high-fat diet results in
increased levels of lipopolysaccharide (LPS), which is a pro-
inflammatory mediator (Holmes et al., 2011). Moreover, chronic
inflammation induced by gut microbes can drive the progression
of colorectal cancer from adenoma to invasive carcinoma (Uronis
et al., 2009). Thus, inflammation can be triggered and modulated
by an altered gut microbiota, and exposure to compounds that
can alter the gut microbiota may induce inflammation in the host.
In this study, we first used 16S rRNA gene sequencing to
examine the effects of sucralose on the gut microbiome of
C57BL6/J mice over a 6-month administration period. Next,
we used metabolomics to profile fecal metabolome changes
associated with a perturbed gut microbiome. Finally, we assessed
several markers of inflammation to define the effects of sucralose
consumption on host tissues. Our results show that sucralose
altered the gut microbiome and associated metabolic profiles,
which may contribute to inflammatory response in the mouse
liver.
MATERIALS AND METHODS
Animals and Sucralose Exposure
Male C57BL/6J mice (∼8 weeks old) purchased from the Jackson
Laboratory (Bar Harbor, ME) were used in this study. Twenty
male mice were housed in the University of Georgia animal
facility for a week before the study and then assigned to the
control or treatment group (ten mice in each group), which
received tap water or sucralose (Sigma-Aldrich, MO) in tap water,
respectively, for 6 months. The concentration of sucralose was 0.1
mg/ml, which was equivalent to the FDA-approved acceptable
daily intake (ADI) in humans (5 mg/kg/day). Fresh solutions
were made every week, and the consumption of water was
measured for both groups. Standard pelleted rodent diet and tap
water were provided to the mice ad libitum, and the mice were
housed in environmental conditions of 22◦C, 40–70% humidity,
and a 12:12 h light:dark cycle before and during the experiment.
Body weight was measured before and after the treatment. Fecal
pellets were collected at baseline and at three and 6 months
of treatment. Mice were euthanized with carbon dioxide and
necropsied after 6 months. All experiments were approved by
the University of Georgia Institutional Animal Care and Use
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Bian et al. Sucralose Alters the Gut Microbiome
Committee. The animals were treated humanely and with regard
for alleviation of suffering.
16S rRNA Gene Sequencing of the Gut
Microbiota
The gut microbiota was investigated using 16S rRNA gene
sequencing in fecal samples at different time points. DNA was
isolated from the feces of individual mice using a PowerSoil
DNA Isolation Kit (MO BIO Laboratories) according to
the manufacturer’s instructions, and the resultant DNA was
quantified and stored at −80◦C until further analysis. The V4
region in the 16S rRNA gene was targeted using the universal
primers 515 (5′-GTGCCAGCMGCCGCGGTAA) and 806 (5′-
GGACTACHVGGGTWTCTAAT). For each sample, 1 ng of the
purified fecal DNA was used as a template for amplification
and then barcoded with specific indexes. The amplified products
were then normalized, pooled and sequenced by an Illumina
MiSeq at the Georgia Genomics Facility. Paired-end 250 ×250
(PE250, v2 kit) reads were generated at a depth of at least
25,000 reads per sample. Geneious 8.1.5 (Biomatters, Auckland,
New Zealand) was used to process the raw fastq files, and the
mate-paired files were trimmed to dispose of bases with an
error probability higher than 0.01 and then merged. The data
were then analyzed using quantitative insights into microbial
ecology (QIIME, version 1.9.1) (Caporaso et al., 2010), and
UCLUST was used to match operational taxonomic units (OTUs)
with 97% sequence similarity against Greengenes database 13.8.
The matched sequences were assigned at five different levels:
phylum, class, order, family and genus. The raw data of controls
and treated-mice have been uploaded into the MG-RAST
server (http://metagenomics.anl.gov/) with the following job
IDs: 317595, 317584, 317588, 317586, 317583, 317589, 317596,
317592, 317585, 317598, 317590, 317599, 317582, 317594,
317591, 317581, 317597, 317580, 317593, and 317587.
Functional Gene Enrichment Analysis
An open-source R package, Tax4Fun, was first used to analyze
the enrichment of functional genes of the microbiome of each
group (Asshauer et al., 2015). The output from QIIME with
a SILVA database extension (SILVA 119) was used for this
analysis. Tax4Fun can survey the functional genes of bacterial
communities based on the 16S rRNA sequencing data and
provide a good approximation to the gene profiles obtained
from metagenomic shotgun sequencing methods. The results
from Tax4Fun were further analyzed using Statistical Analysis
of Metagenomic Profiles (STAMP) (version 2.1.3) (Parks et al.,
2014).
Fecal Metabolomics Analysis
Metabolites in fecal samples collected at 6 months were extracted
using methanol and water as previously described (Lu et al.,
2014). In brief, 20 mg of feces was disrupted in 1 ml of a
methanol/water solution (1:1) with a TissueLyser at 50 Hz for 5
min, followed by centrifugation at 12,000 rpm for 10 min. The
resultant upper phase was collected and dried using a SpeedVac,
and the dried samples were re-suspended in 20% acetonitrile
for MS analysis. Metabolomic profiling was conducted using
a quadrupole-time-of-flight (Q-TOF) 6520 mass spectrometer
(Agilent Technologies, Santa Clara, CA) with an electrospray
ionization source interfaced with an Agilent 1200 HPLC system.
The detailed method for metabolomics was published previously
(Lu et al., 2012). The Q-TOF was calibrated with standard tuning
solution (Agilent Technologies) daily to ensure a mass accuracy
within 5 ppm. A YMC Hydrosphere C18 column was used to
separate the metabolites, and all detectable molecular features in
a mass range of 30–2,000 m/z were captured in the positive mode.
Metabolomic Data Processing and
Metabolite Identification
The data obtained from the HPLC-Q-TOF system were
processed and analyzed as previously described (Lu et al., 2012).
Briefly, the raw.d data were converted to .mzdata format using
MassHunter Workstation software (Agilent), and only signals
with an intensity higher than 1,000 counts were included in
the subsequent analysis. Peak alignment, intensity calculations,
and comparisons between the control and treatment group
were performed using the XCMS Online tools. Significantly
changed molecular features were profiled and searched against
the Human Metabolome Database (HMDB) (http://www.hmdb.
ca) and METLIN (http://metlin.scripps.edu) with a 10-ppm mass
accuracy threshold. The matched exact masses were stored and
used for the generation of MS/MS data to tentatively identify the
metabolites. The matched molecular features were fragmented
using MS/MS in the Q-TOF 6520 mass spectrometer to obtain
the product ions, and the spectra were compared with the HMDB
and METLIN MS/MS database to identify significantly altered
metabolites, with at least two matched fragments within a 200
ppm mass accuracy as the matching threshold.
Quantitative Real-Time Polymerase Chain
Reaction (qPCR)
Liver was first segmented into left lobe, media lobe, right lobe,
and caudate lobe during necropsy. Each liver segment was put
into a 2 ml tube, followed by immediate addition of 1 ml of
RNAlater R
solution (Thermo Fisher Scientific). The tubes were
stored at +4◦C overnight to allow the RNAlater R
solution to
inhibit the RNase before they were transferred to the −80◦C
freezer for storage. Liver samples (right lobe) treated with
RNAlater R
were used to isolate RNA with an RNeasy Mini
Kit (Qiagen, Valencia, CA) according to the manufacturer’s
instructions, and the resultant RNA was digested with a DNA-
freeTM DNA Removal Kit (Thermo Fisher Scientific) to remove
genomic DNA contamination. RNA integrity number (RIN) for
each RNA sample was measured with an Agilent Bioanalyzer.
The RIN typically was >9.0, indicating no RNA degradation
in the samples and processing. Then, cDNA was synthesized
from 1 µg of total RNA using iScriptTM Reverse Transcription
Supermix for RT-qPCR (Bio-Rad Laboratories, CA), and the
products were diluted to 1:5 before use in subsequent reactions.
Quantitative real-time PCR was performed on a Bio-Rad
CFX96 TouchTM Real-Time PCR Detection System using
SsoAdvancedTM Universal SYBR R
Green Supermix (Bio-Rad).
The sequences of the primers used for quantitative PCR were
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Bian et al. Sucralose Alters the Gut Microbiome
as follows: TNF-α, 5-CCCTCACACTCAGATCATCTTCT and
5-GCTACGACGTGGGCTACAG; IL-6, 5-TAGTCCTTCCTA
CCCCAATTTCC and 5-TTGGTCCTTAGCCACTCCTTC;
IL-1β, 5-GCAACTGTTCCTGAACTCAACT and 5-ATCTTT
TGGGGTCCGTCAACT; iNOS, 5-GTTCTCAGCCCAACAATA
CAAGA and 5-GTGGACGGGTCGATGTCAC; MMP-2, 5-CAG
GGAATGAGTACTGGGTCTATT and 5-ACTCCAGTTAAA
GGCAGCATCTAC; MMP-9, 5-ATCTCTTCTAGAGACTGG
GAAGGAG and 5-AGCTGATTGACTAAAGTAGCTGGA;
MMP-13, 5-GTGTGGAGTTATGATGATGT and 5-TGCGAT
TACTCCAGATACTG; and β-actin, 5-CGTGCGTGACATCAA
AGAGAA and 5-TGGATGCCACAGGATTCCAT. All results
were normalized to the β-actin or GAPDH gene (endogenous
control). The fold change in expression over control samples was
calculated using the 11CT method by CFX manager software
(Bio-Rad). The qPCR conditions were 95◦C for 10 min, 40 cycles
of 15 s at 95◦C, 30 s at 60◦C, and 30 s at 72◦C, and a final melting
curve analysis performed by raising the temperature from 65
to 95◦C in 0.5◦C increments for 0.05 s each. Potential genomic
DNA contamination was controlled for by DNase digestion and
the inclusion of a No-RT control, and technical contamination
was controlled for by the inclusion of a No-template control.
Data Analysis
The difference in individual gut bacterial components between
control and sucralose-treated mice at different time points was
assessed with the Mothur software. A two-tailed Welch’s t-test
(p<0.05) was used to compare the difference in metabolites
between the control and sucralose-treated mice. Additionally,
principle component analysis (PCA) was used to examine the
intrinsic clusters and outliers. Partial least squares discriminant
analysis (PLS-DA) and a hierarchical clustering heat map was
used to visualize metabolomic difference in different groups. A
two-tailed Student’s t-test was used to determine the statistical
significance of pro-inflammatory gene expression between the
controls and treated mice.
RESULTS
Sucralose Altered the Developmental
Dynamics of the Gut Microbiome
The gut microbiome is a dynamic system, and its bacterial
composition shifts over time. Maintaining normal developmental
trajectories of the gut microbiome is critical for its functions.
Feces collected from both groups of mice at baseline and
after three and 6 months of administration were employed
to investigate the effects of sucralose on the gut microbiome.
Using 16S rRNA gene sequencing, we found that 14 genera
exhibited different patterns over time in sucralose-treated mice
compared with control mice, as shown in Figure 1. These
bacterial genera exhibited no significant difference in abundance
at baseline but were significantly different after three and/or
6 months of treatment, indicating that sucralose disrupts the
developmental dynamics of gut bacteria. The genera included
Turicibacteraceae Turicibacter,Lachnospiraceae Ruminococcus,
Ruminococcaceae Ruminococcus,Verrucomicrobiaceae
Akkermansia,Staphylococcaceae Staphylococcus,Streptococcaceae
Streptococcus,Dehalobacteriaceae Dehalobacterium,
Lachnospiraceae Anaerostipes,Lachnospiraceae Roseburia,
and unclassified members in Family Clostridiaceae,
Christensenellaceae,Peptostreptococcaceae,Erysipelotrichaceae
and Order Bacillales..
Sucralose Increased the Abundance of
Bacterial Genes Related to
Pro-inflammatory Mediators
We next examined whether the changes in gut microbiome
composition were associated with functional perturbations of
the gut bacteria. Indeed, a number of bacterial functional genes
were enriched in sucralose-treated mice. For example, functional
gene enrichment analysis of the gut microbiome showed that
genes related to bacterial pro-inflammatory mediators were
highly elevated in sucralose-treated mice, as shown in Figure 2.
Specifically, genes related to LPS synthesis were significantly
increased after 6 months of treatment. In addition, multiple genes
related to flagella protein synthesis were increased in sucralose-
treated mice. Likewise, genes involved in fimbriae synthesis
increased in sucralose-treated mice. Numerous bacterial toxin
genes, such as toxic shock syndrome toxin-1 and shiga toxin
subunits, were also elevated in sucralose-treated mice.
Sucralose Changed the Fecal Metabolome
We next conducted metabolomic profiling to examine the
functional impact of sucralose on the fecal metabolome. The
combination in feces of a large quantity of gut bacteria and
their metabolic products creates an ideal biological sample to
assess functional changes in the gut microbiome. A total of
13,611 molecular features were detected in fecal samples, 1,764 of
which were significantly different (p<0.05 and fold change>1.5)
between the sucralose-treated and control mice (Figure 3A),
clearly indicating that sucralose perturbed the fecal metabolome.
A PLS-DA plot (Figure 3B) showed a separation in the molecular
patterns of the two groups, and the hierarchical clustering heat
map (Figure 3C) was consistent with this result. Molecular
features matched with the HMDB and METLIN database were
used for metabolite identification via MS/MS. We tentatively
identified 66 metabolites, including quorum sensing compounds,
amino acids and derivatives, lipids, fatty acids, bile acids, and
nucleic acids, among others (Supplementary Table 1).
Sucralose Altered Quorum Sensing Signals
Bacteria control multicellular behaviors, such as biofilm growth
and development, horizontal gene transfer, host-microbe cross-
talk, and microbe-microbe interactions, by the cell-cell signaling
process known as quorum sensing. Four acyl homoserine
lactones known to be quorum sensing signals (Bainton et al.,
1992; Winson et al., 1995; Passador et al., 1996; Stankowska
et al., 2008; Lade et al., 2014) were identified: N-butanoyl-
l-homoserine lactone, N-(3-oxo-hexanoyl)-homoserine lactone,
N-tetradecanoyl-L-homoserine lactone, and N-pentadecanoyl-L-
homoserine lactone. The reduced abundance of these quorum
sensing signals in sucralose-treated mice (Figure 4) indicates that
sucralose disrupts quorum sensing signaling.
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Bian et al. Sucralose Alters the Gut Microbiome
FIGURE 1 | Sucralose altered the dynamics of gut microbiome development in C57BL6/J mice. Bacterial genera exhibited different patterns over time between the
control and sucralose-treated mice. *p<0.05.
Sucralose Altered Amino Acids and Derivatives
The gut microbiome is highly involved in the synthesis and
regulation of amino acids. Amino acids, such as L-tryptophan,
L-tyrosine, L-leucine, and L-isoleucine, as well as their
derivatives (Table S1) were affected by sucralose treatment.
Four compounds involved in tryptophan metabolism were
identified, including L-tryptophan (Trp), quinolinic acid,
kynurenic acid, and 2-aminomuconic acid, as shown in
Figure 5A. Compared with control mice, Trp, quinolinic acid,
and 2-aminomuconic acid were increased by 1.71-, 5.45-,
and 2.09-fold in sucralose-treated mice, while kynurenic
acid was reduced by 2.45-fold in sucralose-treated mice.
For tyrosine metabolism, though L-tyrosine increased (1.62-
fold), two of its metabolites, p-hydroxyphenylacetic acid and
cinnamic acid, decreased by 4.63- and 1.53-fold, respectively
(Figure 5B).
Sucralose Altered Bile Acids
The gut microbiome can transform primary hydrophilic bile
acids into secondary hydrophilic bile acids in the large intestine
through deconjugation, dehydroxylation, and dehydrogenation.
Bile acids not only facilitate fat and fat-soluble vitamin absorption
and maintain cholesterol homeostasis but are also viewed as
signaling molecules that bind to the nuclear receptor FXR and
the G-protein-coupled receptor TGR5. Several bile acids were
significantly different between the control and sucralose-treated
animals (Figure 6). 3-Oxo-4,6-choladienoic acid was increased
in sucralose-treated mice compared with control mice, while
other bile acids were reduced, including 3β,7α-dihydroxy-
5-cholestenoate, 3α,7β,12α-trihydroxyoxocholanyl-glycine
and lithocholic acid/isoallolithocholic acid/allolithocholic
acid/isolithocholic acid.
Sucralose Induced Elevated
Pro-inflammatory Gene Expression in Liver
As described above, sucralose could increase the production
of bacterial pro-inflammatory mediators, which may cause
inflammatory responses in host tissues after being translocated
into the host circulation. In fact, sucralose-treated mice exhibited
elevated gene expression of pro-inflammatory markers in the
liver (Figure 7), such as matrix metalloproteinase 2 (MMP-2) and
inducible nitric-oxide synthase (iNOS).
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Bian et al. Sucralose Alters the Gut Microbiome
FIGURE 2 | Enrichment of bacterial pro-inflammatory genes after 6 months of sucralose treatment (*p<0.05, **p<0.01), including genes involved in LPS (A),
flagella (B), and fimbriae synthesis (C) as well as toxins (D) and multidrug resistance genes (E).
DISCUSSION
The gut microbiota is a dynamic system, and maintaining a
healthy balance is vital for the host (Nicholson et al., 2012).
Previous studies have demonstrated that changes to the gut
microbiota affect numerous host processes, such as immune
system development and energy metabolism and absorption,
and can also impact diseases in and beyond the GI tract
(Holmes et al., 2011). Xenobiotics in the food or environment
can affect the gut microbiome and host health (Lu et al.,
2014; Suez et al., 2014; Gao et al., 2017). One common
argument used to support sucralose safety is that the majority
of sucralose is not absorbed or metabolized in the body (Grice
and Goldsmith, 2000). However, we demonstrate here that
sucralose can affect the gut microbiome, its metabolic functions
and the host even though it passes through the GI tract
unchanged.
Specifically, we investigated the effect of sucralose
consumption on the gut microbiota and host in mice using
16S rRNA gene sequencing, functional gene enrichment
analysis, metabolomics and real-time PCR. Sucralose
consumption for 6 months altered the gut microbiome
composition, fecal metabolites, and pro-inflammatory gene
expression in the liver. The alterations induced by sucralose
consumption could affect the development of inflammation
and further influence other physiological functions in the
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Bian et al. Sucralose Alters the Gut Microbiome
FIGURE 3 | Sucralose changed the fecal metabolome, as illustrated by the Cloud plot (A), PLS-DA plot (B), and heat map (C). A total of 1,764 molecular features
were significantly different (p<0.05 and fold change>1.5) between sucralose-treated mice and controls.
body. This study provides a new understanding of the
effect of artificial sweeteners on the gut microbiota and
host health.
Sucralose has been shown to be safe using different
endpoints in previous studies, but very few studies have
reported its effects on the gut microbiome and, particularly,
its functions (Grotz and Munro, 2009). In this study, we
examined sucralose-induced gut microbiome functional
perturbation, which may contribute to the development of
systemic inflammation in the host. Altering the gut bacterial
composition may confer an increased risk of developing
inflammation in sucralose-treated mice. For example, among
the 14 changed genera, several were found to be associated
with host inflammation. Ruminococcaceae Ruminococcus,
which were more abundant in sucralose-treated mice in
this study, were shown to be more abundant in colonic
Crohn’s disease samples than in healthy samples in a previous
study (Willing et al., 2010); Streptococcaceae Streptococcus,
Dehalobacteriaceae Dehalobacterium,Lachnospiraceae
Anaerostipes, and Lachnospiraceae Ruminococcus, which
were reduced in sucralose-treated mice, were found to be
negatively associated with inflammation in previous studies
(Willing et al., 2010; Collins et al., 2014; Fernández et al.,
2016; Munyaka et al., 2016). The functional impact of these
altered gut bacteria remains to be further elucidated in the
future. Nevertheless, alterations in gut microbiome composition
may lead to differential functional bacterial metagenomes and
metabolic capacities of the gut microbiome.
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Bian et al. Sucralose Alters the Gut Microbiome
FIGURE 4 | Quorum sensing signals were altered by sucralose consumption. *p<0.05, ***p<0.001.
FIGURE 5 | Amino acids and derivatives altered by sucralose. *p<0.05, **p<0.01, ***p<0.001) (A) tryptophan metabolites; (B) tyrosine metabolites.
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Bian et al. Sucralose Alters the Gut Microbiome
FIGURE 6 | Sucralose altered bile acids in the fecal samples of mice treated with sucralose for 6 months. *p<0.05, **p<0.01.
FIGURE 7 | Sucralose consumption increased the gene expression of inflammatory markers in the liver, as examined by qRT-PCR. The mRNA expression of matrix
metalloproteinase 2 (MMP-2) and inducible nitric-oxide synthase (iNOS) was elevated in sucralose-treated mice. *p<0.05, N.S., no statistical significance.
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Bian et al. Sucralose Alters the Gut Microbiome
Previous studies have demonstrated that functional genes of
the bacterial community are related to 16S rRNA marker genes,
allowing the functional capacities of the gut microbiome to be
surveyed using 16S rRNA gene sequencing (Asshauer et al.,
2015). Using functional gene enrichment analysis, a number
of genes related to bacterial pro-inflammatory mediators were
shown to be significantly increased in the sucralose-treated gut
microbiome, including genes involved in LPS synthesis, flagella
protein synthesis, and fimbriae synthesis as well as bacterial
toxins and drug resistance genes. LPS, flagella, and fimbriae are
known PAMPs that can trigger pathological inflammation in
the host, and various toxins produced by bacteria can induce
toxicity in the host. LPS, a known endotoxin from the outer
membrane of gram-negative bacteria, can initiate inflammatory
events, such as the secretion of pro-inflammatory cytokines like
interleukin-6 or tumor necrosis factor (TNF)-α(de La Serre et al.,
2010). Flagella protein levels are low in a healthy gut, and high
levels of flagella proteins have been shown to be associated with
gut mucosal barrier breakdown and inflammation in previous
studies (Cullender et al., 2013). Fimbriae play an important
role in bacterial adhesion to and invasion of epithelial cells
and are known virulence factors (Nakagawa, 2002). Additionally,
multidrug resistance genes were increased in the sucralose-
treated gut microbiome, and the increase in multidrug resistance
genes and/or multidrug-resistant bacteria may lead to a more
hostile gut environment (Marshall et al., 2009). These data
indicate that 6 months of sucralose consumption increased the
pro-inflammatory products of the gut microbiome and its ability
to potentially induce systemic inflammation.
Likewise, the metabolites identified in fecal samples may be
involved in regulating inflammation. For example, several amino
acids were perturbed in sucralose-treated fecal metabolites in this
study. In particular, we found that tryptophan metabolism was
disrupted by sucralose, and this disruption was related to changes
in the expression of functional genes of the gut microbiome.
As shown in Supplementary Figure 1, several genes related to
tryptophan metabolism were elevated, while the abundance of
tryptophan and its metabolites were altered in the fecal samples.
The four metabolites identified are involved in the kynurenine
pathway, which is the most important tryptophan metabolism
pathway, consuming 95% of the tryptophan in the body
(Keszthelyi et al., 2009). The balance between two metabolites
in this pathway, quinolinic acid, and kynurenic acid, plays an
important role in mediating inflammation and the excitability
of cells such as enteric neurons. Quinolinic acid is pro-
inflammatory and excitotoxic, whereas kynurenic acid is anti-
inflammatory and neuroprotective (Keszthelyi et al., 2009). Here,
we found an elevated level of quinolinic acid and a decreased
level of kynurenic acid. This indicates that sucralose may shift
cells to a pro-inflammatory state. Likewise, tyrosine and two of its
metabolites, p-hydroxyphenylacetic acid and cinnamic acid, have
previously been shown to decrease the production of reactive
oxygen species (ROS) in neutrophils (Beloborodova et al.,
2012), and the reduced level of these compounds in our study
indicated that ROS levels may be increased in sucralose-treated
mice. Bacterial antioxidative enzyme genes, such as catalase
and catalase-peroxidase, which respond to ROS, were also
significantly enriched in sucralose-treated mice (Supplementary
Figure 2). ROS can stimulate the release of pro-inflammatory
cytokines (Chapple, 1997); therefore, the decrease in the two
tyrosine metabolites may contribute to the development of a pro-
inflammatory state. Additionally, secondary bile acids that have
FIGURE 8 | Proposed functional link between sucralose-induced gut microbiota alterations and host inflammation. Sucralose perturbs the gut microbiome and its
metabolic functions, inducing the enrichment of bacterial pro-inflammatory mediators, and disrupting metabolites involved in inflammation regulation. Together, these
consequences may contribute to the induction of liver inflammation in the host.
Frontiers in Physiology | www.frontiersin.org 10 July 2017 | Volume 8 | Article 487
Bian et al. Sucralose Alters the Gut Microbiome
antimicrobial effects were decreased, which may allow the growth
of pathogens (Begley et al., 2005).
Pro-inflammatory mediators, such as LPS, and metabolites
can translocate into host circulation and tissues, leading to
systemic inflammatory response (de La Serre et al., 2010).
In accordance with this expectation, real-time PCR results
showed that MMP-2 and iNOS expression was elevated in the
liver of sucralose-treated mice. MMP-2 is strongly associated
with inflammatory responses, because it can cleave and
activate TNF-αand IL-1β, which are both pro-inflammatory
cytokines that contribute to the induction of inflammation
(Medina and Radomski, 2006; Wang et al., 2006). Likewise,
iNOS-derived NO regulates pro-inflammatory genes and
significantly contributes to inflammatory liver injury. iNOS
exerts numerous effects associated with the progression of
inflammatory conditions in multiple liver diseases, such as
increasing the liver inflammatory response, promoting the
induction of liver tumors and contributing to liver fibrosis
caused by a chronic viral infection (Sass et al., 2001; La
Mura et al., 2014). The expression of both MMP-2 and iNOS
was found to be increased in the liver of sucralose-treated
mice compared with control mice, indicating that sucralose
exposure increases the risk of developing inflammation in
the liver. Notably, most of the sucralose consumed passes
through the GI tract unabsorbed and unchanged (Roberts
et al., 2000); therefore, the inflammatory response observed
in the liver was unlikely to be stimulated by sucralose
directly.
Taken together, as illustrated in Figure 8, our data show
that 6-month sucralose consumption at human ADI alters the
gut microbiome and its functions in mice. In particular, the
enrichment of gut microbial pro-inflammatory genes and fecal
metabolites suggests that sucralose alters the gut environment to
release more pro-inflammatory mediators and alter functional
metabolites, which may contribute to the increased expression
of pro-inflammatory markers in the liver, such as iNOS and
MMP-2. Notably, while the majority of ingested sucralose
passes through the GI tract unabsorbed, it does disrupt
the gut microbiota and its functions; therefore, our results
highlight the role of sucralose-gut microbiome interaction
in regulating host health-related processes, such as chronic
inflammation.
There are a few limitations associated with this study. First,
we only assessed inflammatory response in the liver of sucralose-
treated mice by RT-PCR. Examination of host response using
other endpoints and methods, such as circulating LPS and
histological assessment, in related samples and tissues would
be needed to better characterize the effects of sucralose in
the body. Second, we conducted experiments using a single
dose of sucralose at the human ADI, while human intake of
sucralose is typically lower than this concentration. Our ongoing
study using multiple human-relevant doses aims at better
understanding time- and dose-dependent effects of sucralose on
the gut microbiome and host. Third, the enrichment analysis
of functional bacterial genes was performed based on the
16S rRNA sequencing data. Metagenomic shotgun sequencing
and/or metatranscriptomics will further shed light on sucralose-
induced functional perturbation of the gut microbiome. Finally,
the identification of altered metabolites was based on the
matching with the metabolite database. Future validation of key
metabolites of interest with authentic compounds is warranted.
Likewise, a more accurate quantitative analysis of altered
metabolites using stable isotope labeled standards should be
conducted.
AUTHOR CONTRIBUTIONS
XB, HR, and KL designed the study. XB, BG, LC, and PT
acquired, analyzed and interpreted the data. XB, PT, HR, and
KL drafted and critically revised the manuscript, approved the
version to be published, and are accountable for all aspects of the
work.
FUNDING
This research was partially supported by the University of
Georgia, University of North Carolina at Chapel Hill and
NIH/NIEHS (R01ES024950).
SUPPLEMENTARY MATERIAL
The Supplementary Material for this article can be found
online at: http://journal.frontiersin.org/article/10.3389/fphys.
2017.00487/full#supplementary-material
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Conflict of Interest Statement: The authors declare that the research was
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Copyright © 2017 Bian, Chi, Gao, Tu, Ru and Lu. This is an open-access article
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