Short-term dietary methionine supplementation affects one-carbon metabolism and DNA methylation in the mouse gut and leads to altered microbiome profiles, barrier function, gene expression and histomorphology
Miousse et al. Genes & Nutrition
Short-term dietary methionine supplementation affects one-carbon metabolism and DNA methylation in the mouse gut and leads to altered microbiome profiles, barrier function, gene expression and histomorphology
Isabelle R. Miousse 0
Rupak Pathak 2
Sarita Garg 2
Charles M. Skinner 0
Stepan Melnyk 1
Oleksandra Pavliv 1
Howard Hendrickson 2
Reid D. Landes 6
Annie Lumen 5
Alan J. Tackett 1 4
Nicolaas E.P. Deutz 3
Martin Hauer-Jensen 2
Igor Koturbash 0
0 Department of Environmental and Occupational Health, University of Arkansas for Medical Sciences , 4301 W. Markham Str., Slot 820-11, Little Rock, AR 72205-7199 , USA
1 Department of Pediatrics, University of Arkansas for Medical Sciences , Little Rock, AR 72205 , USA
2 Department of Pharmaceutical Sciences, University of Arkansas for Medical Sciences , Little Rock, AR 72205 , USA
3 Department of Health and Kinesiology, Center for Translational Research on Aging and Longevity, Texas A&M University, College Station , TX , USA
4 Department of Biochemistry, University of Arkansas for Medical Sciences , Little Rock, AR , USA
5 Division of Biochemical Toxicology, National Center for Toxicological Research, U.S. Food and Drug Administration , Jefferson, AR , USA
6 Department of Biostatistics, University of Arkansas for Medical Sciences , Little Rock, AR 72205 , USA
Background: Methionine, a central molecule in one-carbon metabolism, is an essential amino acid required for normal growth and development. Despite its importance to biological systems, methionine is toxic when administered at supra-physiological levels. The aim of this study was to investigate the effects of short-term methionine dietary modulation on the proximal jejunum, the section of the gut specifically responsible for amino acid absorption, in a mouse model. Eight-week-old CBA/J male mice were fed methionine-adequate (MAD; 6.5 g/kg) or methioninesupplemented (MSD; 19.5 g/kg) diets for 3.5 or 6 days (average food intake 100 g/kg body weight). The study design was developed in order to address the short-term effects of the methionine supplementation that corresponds to methionine dietary intake in Western populations. Biochemical indices in the blood as well as metabolic, epigenetic, transcriptomic, metagenomic, and histomorphological parameters in the gut were evaluated. Results: By day 6, feeding mice with MSD (protein intake <10% different from MAD) resulted in increased plasma (2.3-fold; p < 0.054), but decreased proximal jejunum methionine concentrations (2.2-fold; p < 0.05) independently of the expression of neutral amino acid transporters. MSD has also caused small bowel bacteria colonization, increased the abundance of pathogenic bacterial species Burkholderiales and decreased the gene expression of the intestinal transmembrane proteins-Cldn8 (0.18-fold, p < 0.05), Cldn9 (0.24-fold, p < 0.01) and Cldn10 (0.05-fold, p < 0.05). Feeding MSD led to substantial histomorphological alterations in the proximal jejunum exhibited as a trend towards decreased plasma citrulline concentrations (1.8-fold, p < 0.07), as well as loss of crypt depth (by 28%, p < 0.05) and mucosal surface (by 20%, p < 0.001). (Continued on next page)
(Continued from previous page)
Conclusions: Together, these changes indicate that short-term feeding of MSD substantially alters the normal gut
physiology. These effects may contribute to the pathogenesis of intestinal inflammatory diseases and/or sensitize the
gut to exposure to other stressors.
Methionine, a central molecule in one-carbon
metabolism, is an essential amino acid required for normal
growth and development [
]. It is indispensable for
protein synthesis and the production of polyamines .
Furthermore, methionine is a key regulator of stress
resistance and is a precursor for S-adenosylmethionine
(SAM), the principal donor of methyl groups, as well as
cysteine and glutathione [
16, 19, 46
]. Studies using a
neonatal piglet model have demonstrated the high
importance of dietary methionine especially during early
stages of life [
8, 48, 63
]. A number of studies report
beneficial effects of methionine dietary supplementation
on gut function, including improvement of the mucosal
villus architecture, as well as methionine
intakeassociated decreased risk of colon cancer [
7, 8, 49, 76
Alterations to one-carbon metabolism and the
methionine cycle are linked to a number of diseases, including
cardiovascular disease and cancer [
16, 22, 68
Despite the importance of methionine to biological
systems, it is by far the most toxic amino acid [
The formation of methanethiol-cysteine disulfides is
thought to cause methionine toxicity ; however, this
alone cannot explain the wide range of health outcomes
associated with an increased consumption of
methionine, including growth retardation, infertility,
accumulation of hemosiderin, inflammatory responses, liver
damage, and cardiovascular disease (reviewed in [
Some recent studies indicate that methionine
supplementation accelerates oxidative stress and activates
NFkB in the mouse liver [
]. Aissa and colleagues have
reported that, in the mouse model, methionine dietary
supplementation increased hepatic levels of
S-adenosylL-homocysteine and homocysteine, altered expression of
one-carbon and lipid metabolism genes, and caused lipid
accumulation in the liver [
Although liver is considered a major organ for
methionine metabolism, it becomes increasingly recognized
that the intestine also serves as a significant site of
dietary methionine metabolism [
7, 17, 63, 66
]. However, the
exact fate of dietary methionine in the proximal
intestine, the section of the gut specifically responsible for
amino acid absorption, remains to be investigated.
Furthermore, the host-intestinal microbiome axis adds
an additional layer of complexity, given the tight
relationship that exists between the host’s and
microbiome’s amino acid metabolism [
2, 52, 57
]. Moreover, it
has been demonstrated that the production of
xenometabolites is under the influence of the host’s diet [
Therefore, the aim of this study was to investigate the
effects of the short-term methionine dietary modulation
on the proximal jejunum in a mouse model.
Animals and diets
Eight-week-old CBA/J male mice were purchased from
Jackson Laboratory (Bar Harbor, ME, USA). The animals
were housed at the University of Arkansas for Medical
Sciences (UAMS) animal facility with a 12 h:12 h dark/
light cycle. The experimental protocols were reviewed
and approved by the Institutional Animal Care and Use
Committee (IACUC) at UAMS. Animals were given a
1week acclimation period before the experiment
commenced receiving methionine-adequate diet (MAD).
After that, animals were randomly divided into two
groups where half of the animals continued receiving
MAD (n = 10), while the second half of the animals was
fed methionine-supplemented diet (MSD) (n = 10) for
3.5 or 6 consecutive days. The study design was
developed in order to address the short-term effects of the
methionine supplementation that correspond to
methionine dietary intake in Western populations. Water and
food were provided ad libitum. All diets were purchased
from Envigo (Madison, WI, USA). The detailed
composition and nutrient information for each diet are provided
in Tables 1 and 2. Animals were monitored on a daily
basis; food and water consumption and body weights
were recorded daily.
On days 3.5 and 6, animals were anesthetized with
isoflurane (3% in oxygen) and retroorbital bleeding in
EDTA-coated tubes was performed in order to obtain
blood samples. Blood was centrifuged at 10,000×g for
2 min at room temperature. Plasma was collected,
flashfrozen in liquid nitrogen, and stored at −80 °C for
subsequent analyses. Anesthetized mice were euthanized by
cervical dislocation and intestines were collected
immediately for the metabolic, molecular, and
Mineral mix, AIN-76 (170915)
Calcium phosphate, dibasic
L-histidine HCl, monohydrate
Analysis of methionine plasma concentrations
Blood was centrifuged immediately after animal
bleeding, and serum was stored at −80 °C conditions. Plasma
methionine concentrations were determined using the
commercially available EZ:fast amino acid kit for
physiological amino acids (Phenomenex; Torrance, CA, USA).
Samples (50 μl) were first prepared for derivatization
using a solid phase extraction step followed by a
derivatization and liquid/liquid extraction. Derivatized amino
acids were extracted into a mixture of
chloroform:isooctane (1:2). The top organic layer was removed and
evaporated to dryness under a gentle stream of nitrogen
at room temperature. The residue was reconstituted in
100 μl of mobile phase and injected (1 μl) onto the
LCMS/MS system. Analyte separation was achieved using a
gradient elution profile provided with the EZ:fast kit on
a 250 × 2.0 mm EZ:fast analytical column. The flow rate
was 0.25 ml/min. The total run time was 17 min.
Tissue determination of analytical components of methionine metabolism
Proximal jejunum samples were flushed with 1X PBS and
flash-frozen to further determine levels of methionine,
Sadenosylmethionine (SAM), S-adenosylhomocysteine
(SAH), total and free homocysteine and homocystine,
cysteine, cystine, as well as reduced (GSH) and oxidized
(GSSG) glutathione using an HPLC-EC method, as
previously described [
Nucleic acids extraction
RNA and DNA were extracted simultaneously from
flash-frozen tissue using the AllPrep DNA/RNA
extraction kit (QIAGEN, Valencia, CA, USA) according to the
manufacturer’s protocol (including RNase and DNase
digestion for DNA and RNA, respectively). DNA and RNA
concentrations and integrity were analyzed by the
Nanodrop 2000 (Thermo Scientific, Waltham, MA, USA). For
DNA, only samples with the 260/280 ratios between 1.8
and 1.9 and the 260/230 ratios above 1.5 were
considered for further molecular analyses. For RNA, only
samples with the 260/280 ratios between 1.95 and 2.05 and
the 260/230 ratios above 1.5 were considered for further
Analysis of intra-intestinal mRNA levels of neutral amino acid transporters
RNA was extracted as described above. cDNA was
synthesized using the SuperScript reverse transcription kit
(Life Technologies, Carlsbad, CA, USA) according to the
manufacturer’s protocol. Quantitative real-time PCR
(qRT-PCR) was performed with Taqman Universal
Master Mix (Life Technologies) according to the
manufacturer’s protocol. Primers were added at a final
concentration of 5 μM (Additional file 1). Expression of
mRNA targets was normalized to the internal control
genes Hprt and Gapdh and expressed as fold change
according to the ΔΔCt method.
Analysis of LINE-1 DNA methylation
Recent advances in computational biology have led to
classification of LINE-1 elements based on their
evolutionary age and respective 5′-UTR sequences [
this study, we assessed the DNA methylation status of
seven LINE-1 elements that belong to evolutionary the
youngest A-type promoter. LINE-1 families’ consensus
sequences were obtained from the Genetic Information
Research Institute (GIRI) Database:
]. Then, the 5′-UTRs of seven LINE-1 elements
were analyzed using NEBcutter® (http://nc2.neb.com/
NEBcutter2/). The five most frequent CpG sites that can
be cleaved by the methylation-sensitive restriction
enzymes (AciI, BstUI, HhaI, HpaII, and SmaI) were
identified and individual RT-PCR assays for each LINE-1
element were developed and validated. Analysis of the
LINE-1 DNA methylation was performed as previously
]. Briefly, 1 μg of genomic DNA was
digested with 1 U of SmaI in 1X CutSmart buffer at
25 °C for 2 h. This was followed by a 16 h digestion at
37 °C in the presence of 1 U of the HpaII, HhaI, and
AciI in 1X CutSmart buffer. The digestion was finalized
by adding 0.5 U of BstUI in 1X CutSmart buffer for 4 h
at 60 °C (New England Biolabs, Ipswich, MA, USA).
Digested DNA was then analyzed by qRT-PCR on a
ViiA 7 real-time PCR system (Applied Biosystems,
Forrest City, CA, USA). DNA samples not digested with
the restriction enzyme mix served as a positive control,
while samples lacking the specific primers for DNA
amplification and/or DNA template served as negative
controls. The Ct was defined as the fractional cycle
number that passes the fixed threshold. The Ct values
were converted into the absolute amount of input DNA
using the absolute standard curve method and further
normalized towards readings from the respective to
each LINE-1 element ORF1 region that lacks CpG sites.
Assays for determination of 5′-UTR LINE-1 DNA
methylation are provided in Additional file 1.
Gene expression analysis of mRNA levels of tight junction-related proteins
RNA was extracted using the QIAGEN DNA/RNA
extraction kit (QIAGEN) according to the
manufacturer’s instructions. Mouse tight junctions PCR array
(SA Biosciences, array #PAMM143Z) was used to
analyze the expression of genes involved in the
regulation of tight junction-related proteins according to
the manufacturer’s protocol.
Gram staining of the intestinal microbiota
The proximal jejunum slides were deparafinized by
placing them in a 60 °C oven for 15 min. The slides were
then placed in xylene for 5 min twice, followed by 3 min
in 100% ethanol twice. The slides were then immersed
in 90% ethanol for 3 min, then in 80% ethanol for 3 min.
The slides were rinsed under tap water for 30 s and
placed in deionized water for 30 min. The slides were
blotted and then stained for 30 s with Gram stain (Gram
stain for tissue kit, Sigma-Aldrich, St. Louis, MO, USA).
The Gram stain was drained off and the slides rinsed by
immersion in deionized water. Gram’s iodine was added
to the slides for 5 min, then drained and rinsed by
immersing in deionized water. The slides were thoroughly
differentiated in absolute alcohol then rinsed again in
deionized water before adding saffranin for 30 s. Slides
were drained and rinsed in deionized water and then
blotted. Finally, tartrazine solution was added for 10 s
then blotted. The slides were rinsed twice in 100%
ethanol for 2 min, then in xylene for 2 min. The cover slip
was mounted with permount (Fisher Scientific,
Pittsburgh, PA, USA), and the slides were allowed to dry
Analysis of the 16S rRNA in the proximal jejunum
Section of the proximal jejunum was cut with the sterile
pair of scissors and flash-frozen in liquid nitrogen. DNA
was extracted under sterile conditions as described above.
Amplification of the bacterial 16S DNA gene was
performed from 5 ng of the proximal jejunum gDNA using
the following set of primers Fw: ACTCCTACGGGAGG
CAGCAGT and R: TATTACCGCGGCTGCTGGC [
Next generation sequencing of gut microbiota
Total intestinal DNA was extracted using the DNeasy
Blood and Tissue Kit (QIAGEN). The extracted DNA
analyzed by NanoDropTM 2000 (ThermoScientific) and
1% agarose gel electrophoresis (in TBE 0.5 X) and sent
to Research and Testing Laboratories for 16S ribosomal
RNA gene sequencing using the Illumina MiSeq System
(Research and Testing Laboratories, Lubbock, TX, USA)
as described before [
16S rRNA genes were amplified by universal primers
357wF: CCTACGGGNGGCWGCAG and 785R: GAC
TACHVGGGTATCTAATCC using the Qiagen
HotStarTaq Master Mix (Qiagen). Next generation
sequencing was performed on the MiSeq platform
(Illumina). Samples were amplified for sequencing in a
two-step process. Primers for the first step were
constructed using 357F-785R with the Illumina i5 and i7
sequencing primers added to the 5′-end of each,
respectively. Products from the first amplification were
added to a second Polymerase Chain Reaction (PCR)
step based on qualitatively determined concentrations
(amplicons were run on 2% ethidium bromide gel, gel
bands were scored, and a volume of products was
added to the second PCR based on the scores). Primers
for the second PCR step were designed using Illumina
Nextera PCR primers with 8 bp dual indices.
Amplification products were then visualized with eGels
(Life Technologies). After that, the products were
pooled equimolar and each pool was then size-selected
in two rounds using Agencourt AMPure XP
(BeckmanCoulter) in a 0.7 ratio for both rounds. Size-selected
pools were then quantified using the Qubit 2.0
florometer (Life Technologies) and loaded on an Illumina
MiSeq 2 × 300 flow cell at 10 pM.
After sequencing, all failed sequence reads, low-quality
sequence ends, tags and primers as well as any
nonbacterial ribosome sequences and chimeras were
removed using the UCHIME chimera detection software
in de novo mode [
]. To curate the short (b150 bp)
reads, sequences with ambiguous base calls, and
sequences with relatively long homopolymers (N6 bp)
were also removed. To determine the identity of bacteria
in the remaining sequences, sequences were denoised,
assembled into OTU clusters (97% identity) using the
UPARSE algorithm [
], and then globally aligned using
the USEARCH global algorithm [
] against a database
of high-quality 16S rRNA bacterial gene sequences
compiled by RTL Genomics (Lubbock, TX) to determine
taxonomic classifications. After OTU selection was
performed, a phylogenetic tree was constructed in Newick
format from a multiple sequence alignment of the OTUs
done in MUSCLE [
] and generated in FastTree
]. Based upon the generated OTU table and
taxonomy file, the bacteria were classified at the
appropriate taxonomic levels. The percentages of sequences
assigned to each bacterial phylogenetic level were
individually analyzed for each pooled sample providing
relative abundance information within and among the
individual samples. All data have been uploaded to the
publically available database
Analysis of citrulline plasma concentrations
Whole blood was collected from the retroorbital sinus
into EDTA-coated tubes (Fisher Scientific). Plasma was
obtained by centrifugation at 12,000 RPM for 5 min
at 4 °C and stored at −80 °C for further analysis.
Citrulline plasma levels were determined using the
high throughput liquid chromatography-tandem mass
spectrometry (LC-MS/MS) methodology, as previously
]. Briefly, plasma samples (10 μl)
were treated with 490 μl acetonitrile:water:formic acid
(85:14.8:0.2 v/v) containing internal standard (2 μM).
After mixing gently, the samples were covered,
allowed to stand for 5 min, and the filtrate was
collected under vacuum.
Intestinal crypt colony assay
Microcolony crypt cell survival was performed as
previously described [
]. Briefly, groups of mice fed
either MAD or MSD diets were humanly euthanized on
days 3.5 and 6, segments of proximal jejunum were
obtained, fixed, and H&E stained. Surviving crypts, defined
as crypts containing 10 or more adjacent chromophilic
non-Paneth cells, were counted in transverse
crosssections. Four circumferences were scored per mouse
and microcolony survival was expressed as the average
number of crypts per circumference, with the average
from each mouse considered as a single value for
Mucosal surface area analysis
Previously, our laboratory measured mucosal surface
area in vertical sections using a stereologic projection/
cycloid method as described by Baddeley et al. [
was adapted by us to our model system [
method does not require assumptions about the shape
or orientation of the specimens and thus circumvents
problems associated with most other procedures for
surface area measurement. Using the same principle, we
developed an automated software to measure intestinal
mucosal surface area in vertical H&E–stained sections of
the jejunum by using a computer-assisted image analysis
program (Image-Pro Premier, Meyer Instruments Inc.,
Houston, TX, USA). All measurements were done with a
10× objective lens and a total of three to five areas were
measured from each intestinal segment.
All data are presented as mean ± standard error of
mean(s). Statistically significant differences for each
treatment compared to the control (at α = 95%) were
assessed using Student’s t test. Statistical analyses were
performed using GraphPad Prism 6 (GraphPad Software
Inc. LaJolla, CA, USA).
Effects of MSD on animal body weight and food and water consumption
Feeding mice MSD initially led to small losses in the
body weights; however, at the end of the experiment
(day 6), the difference between the mice fed MSD and
MAD was not detectable (Additional file 2). Feeding
MSD did not affect significantly food or water
consumption throughout the experiment (data not shown).
MSD causes imbalance between the methionine tissue and plasma concentrations
Mice fed MSD were characterized by significantly
elevated plasma methionine concentrations. Specifically, at
day 3.5, methionine plasma concentrations were 4.2-fold
(p < 0.05) higher in the mice fed MSD compared to the
mice fed MAD. Methionine plasma concentrations
remained elevated at day 6 although to a lower extent
(2.3-fold, p < 0.054) (Fig. 1a). At the same time, the
proximal jejunum methionine tissue concentrations did not
increase at day 3.5 and were substantially decreased
(0.45-fold, p < 0.05) at day 6 (Fig. 1b).
MSD does not affect the expression of neutral amino acid transporters
In order to investigate the mechanisms of the imbalance
between the plasma and intestinal methionine
concentrations, first we analyzed the expression of a number of
genes, implicated in the transport of neutral amino
acids, and methionine in particular—Lat1, Lat2, and
]. We did not identify any significant
differences in the expression of those genes between the mice
fed MAD and MSD (Fig. 1c).
MSD-induced changes in the intestinal microbiome
A number of recent studies demonstrated that shifts in
the gut microbiome may affect the levels of circulating
blood metabolites [
]. In addition, methionine has
been generally recognized as a key molecule in the
metabolism of the intestinal flora [
]. Therefore, we then
addressed the effects of MSD on the mouse intestinal
Feeding mice a diet with the excess methionine for
6 days stimulated bacterial proliferation in the murine
proximal jejunum (Fig. 2a). We have confirmed these
findings with the 16S rRNA-based qPCR, where the
significant (2.1-fold, p < 0.05) increase in the proximal
jejunum of mice fed MSD was observed (Fig. 2b).
The next generation sequencing of the gut
microbiome was done with the sample size of 3/group and
returned an average of 20,562 classified reads per
sample. There was an average of 127 observed OTU per
sample. The PCA analysis showed a complete separation
between the MAD and MSD groups. Axis 1 accounts for
half of the variation, and axis 2 accounts for 27%
(Additional file 3). The rarefaction plot of species
richness, Chao1 richness, and Shannon diversity all pointed
to a decrease in the number of species detected in MSD
compared to MAD (Additional file 4). Furthermore,
MSD caused substantial shifts in the intestinal
microbiome at both the phylum and lower taxonomic levels.
Specifically, MSD significantly decreased the proportion
of firmicutes in comparison to MAD. At the lower
taxonomic levels, MSD induced a significant decrease in
Clostridiales, which are heavily involved in intestinal
metabolism, and concomitantly increased the abundance of
Burkholderiales. (Fig. 2c).
MSD causes substantial changes in the expression of markers of intestinal inflammation and tight junctionsrelated proteins
Shifts in intestinal microbiota profiles may cause intestinal
inflammation and affect the expression of tight
junctionrelated proteins leading to increased intestinal permeability
18, 33, 69
]. Furthermore, modulation of the methionine
dietary intake has recently been reported to affect the
expression of the intestinal tight junction-related proteins
]. Gene expression analysis revealed a non-significant
trend towards increase (2.6-fold, p < 0.2) in the expression
of Tnfα in the proximal jejunum of mice fed MSD,
compared to MAD-fed mice on day 6. Furthermore, a number
of tight junction-related proteins were found to be
differentially regulated as a result of MSD. Specifically,
feeding mice MSD decreased the expression of the
transmembrane proteins—claudins Cldn8 (0.18-fold, p < 0.05),
Cldn9 (0.24-fold, p < 0.01), and Cldn10 (0.05-fold, p < 0.05)
(Table 3). Additionally, MSD caused decreases in the
MAD methionine-adequate diet. *p < 0.05; **p < 0.01
expression of G-protein signaling gene Gnai1 (0.36-fold, p
< 0.05) and protein kinase Mpp5 (0.51-fold, p < 0.05).
MSD causes alterations in the methionine cycle and DNA methylation
Because methionine is a key molecule in the one-carbon
metabolism and methionine cycle particularly,
alterations in tissue methionine concentrations may
subsequently affect all downstream metabolites. Indeed, MSD
significantly affected not only the intestinal tissue
methionine concentrations, but the entire methionine cycle.
While at day 3.5, only small changes were observed and
limited primarily to increased levels of SAH and cysteine
and subsequently SAM/SAH and cysteine/cystine ratios,
more pronounced changes were observed at day 6
(Table 4). At this time-point, mice fed MSD were
characterized by substantially (over twofold) decreased levels
of intra-intestinal methionine, followed by decreased
concentrations of SAM, cysteine, and GSH, leading to
skewed SAM/SAH, cysteine/cystine and GSH/GSSG
Altered levels of SAM may further affect the process
of DNA methylation, since SAM serves as a primary
donor of methyl groups. By covering ~20% of
mammalian genomes, LINE-1 elements are the most abundant
transposable elements in the living organisms whose
expression is under a tight control of DNA methylation
]. Therefore, their methylation status has generally
been recognized as a surrogate marker for global DNA
methylation status [
Here, we identified that administration of MSD
significantly shifted the patterns of DNA methylation of
LINE-1 elements in the mouse proximal jejunum
(Fig. 3). This effect was dependent on the evolutionary
age of the elements, where the evolutionary younger
(hence, more methylated [
]) LINE-1 elements were
hypomethylated, while the evolutionary elder LINE-1
elements showed tendency towards DNA
hypermethylation (r = 0.1483, p = 0.007).
MSD affects normal intestinal histomorphology
Because of the substantial alterations to one-carbon
metabolism and the methionine cycle, we hypothesized that
these changes may result in impaired protein synthesis
and thus result in decreased enterocyte renewal
properties of the mouse gut.
Citrulline is a non-coding amino acid and an
endproduct of proximal jejunum-associated enterocytes.
Therefore, plasma concentrations of citrulline serve as
a well-validated surrogate biomarker for the functional
enterocyte mass [
]. By day 6 of feeding mice MSD,
the trend towards decreased plasma citrulline
concentrations was identified (1.8-fold, p < 0.07) when
compared to mice fed MAD (Fig. 4a). This finding may
suggest a decrease in the proximal jejunum total
MAD methionine-adequate diet; *p < 0.05
Indeed, decreased methionine tissue concentrations that
lead to impaired protein synthesis have substantially
affected the normal intestinal histomorphology. As evident
from Fig. 4, a ~ 30% decrease in the functional crypts was
observed in mice fed MSD by day 6. Similarly, MSD
substantially decreased the mucosal surface area in the mouse
proximal jejunum compared MAD-fed mice at both
timepoints (by 20%, p < 0.001) (Fig. 4c).
Accumulating evidence indicates that the essential
amino acid methionine may exert a certain degree of
toxicity when administered at supra-physiological levels
10, 37, 65
]. At the same time, due to fortification of
grains and high supplemental levels, consumption of the
methyl donor pathway components, including
methionine, substantially grew in recent decades [
Furthermore, given that the consumption of
supraphysiological amounts of methionine is common in
Western populations [
] and the fact that
methionine has been proposed as a prospective radiomitigator
], investigating the potential methionine-induced
gastrointestinal toxicity is highly important.
In this study, we aimed to examine the effects of the
short-term feeding of MSD on the mouse proximal
jejunum. This section of the gut serves as a primary site
of amino acid absorption and is characterized by the
high rates of cellular proliferation and intense protein
]. The diet used in our study has been
chosen because its methionine concentration (threefold
over the methionine concentration in the MAD) is
considerably translational to the 2–3.3-fold increased
protein methionine intake in current Western populations
]. This diet has been utilized extensively in the
past and is not known to cause significant toxicity in the
In our mouse model, MSD had a transitory effect on
the body weight, leading to slightly decreased weights on
days 2-4, without significant changes in the food or
water intake between the MSD and MAD fed animals.
This may be potentially explained by the physiological
adaptation to the new diet.
Feeding mice MSD has led to an unexpected loss of
the methionine intra-intestinal tissue concentrations,
while the plasma methionine concentrations were
elevated throughout the study. This paradoxical imbalance
between the plasma and tissue concentrations was not
due to the impaired function of the neutral amino acid
transporters, as their mRNA abundance remained
unchanged. Although we cannot exclude the
posttranscriptional inhibition of the transporters, it is very
unlikely that a nearly twofold decrease in the
intraintestinal methionine concentrations is caused by a
substantially decreased transport, given a four-fold increase
in the methionine plasma concentrations at the same
To further explore this phenomenon, we first
sought to investigate the effect of MSD on the gut
microbiome. Methionine is of particular importance
for bacteria that are capable of accumulating
methionine against a concentration gradient, use
evolutionarily acquired diverse methionine biosynthesis pathways,
and are significant contributors to their host’s
methionine metabolism [
]. An increase in the dietary
methionine intake would subsequently result in an
increased amount of methionine in the lumen and
provide an excellent source of fuel for rapid bacterial
proliferation that was confirmed in our study by the
intra-intestinal Gram staining. Because the Gram
staining is strongly biased towards Gram-positive
bacteria, we have confirmed these findings by analysis
of the 16S rRNA in the proximal jejunum of mice.
Furthermore, MSD has led to substantial shifts in the
Intestinal barrier function is critical for maintaining
not only the gut health, but the normal function of the
entire organism. Tight junction-related proteins play a
central role in this barrier function controlling the
intestinal permeability [
]. Observed in our study, the
MSD-induced dramatic loss in the expression of
transmembrane proteins (claudins) suggests the disruption of
the intestinal barrier that can lead to the paracellular
transport of water, electrolytes, and amino acids, as well
as bacterial translocation and development of chronic
inflammation. Furthermore, it is becoming increasingly
recognized that the increase in intestinal permeability,
mediated by altered function of the tight
junctionrelated proteins, plays a critical role in the pathogenesis
of numerous diseases, including inflammatory bowel
disease, irritable bowel syndrome, and celiac disease
(reviewed in ).
Decreased tissue concentrations of methionine have
inevitably led to alterations in one-carbon metabolism
pathways. A number of down-stream metabolites in the
methionine cycle were affected, including SAM, cysteine,
and glutathione. Of particular interest are the decreased
levels of SAM paralleled by the increased levels of SAH
that have resulted in a skewed SAM/SAH ratio with the
shift towards SAH. This probably led to SAM’s decreased
ability to donate its methyl groups for DNA methylation,
which is of critical importance in rapidly proliferating
organs such as the proximal jejunum. We used the
methylation status of the 5′-UTR of LINE-1 elements as a
measurement of DNA methylation. Given the overall
genomic abundance of LINE-1 elements that cover ~20% of
the mammalian genomes, their methylation status is
generally considered as a surrogate biomarker of DNA
]. Furthermore, various environmental stimuli
may adversely affect the DNA methylation status of
]. Because substantial differences may be detected
between the methylation status of different LINE-1
elements based on their evolutionary age [
], we have
addressed the DNA methylation in the 5′-UTRs of six
LINE-1 families that substantially differ by their
evolutionary age (from 0.21 MYR to 4.33 MYR). Interestingly, small
losses in DNA methylation were observed in the
evolutionary the youngest LINE-1 element (L1MdA_I) that was
previously characterized as the most methylated among
the LINE-1 elements [
]. At the same time, DNA
hypermethylation was observed in the evolutionary older
elements, reaching its maximum in the L1MdA_VI element.
It has been shown that the loss of DNA methylation
occurs primarily from the evolutionary younger elements,
while DNA hypermethylation occur primarily at the older,
more demethylated elements as a result of exposure to
ionizing radiation [
45, 55, 62
]. While the loss of L1MdA_I
DNA methylation may be explained by the decreased
SAM availability to donate its methyl groups, the DNA
hypermethylation phenomenon in the older elements
would require further investigation.
Feeding mice MSD induced significant structural
alterations in the intestinal wall which exhibited as decreased
intestinal mucosal surface length, diminished crypt
depth, and trends towards reduced plasma
concentrations of the enterocyte metabolic end-product citrulline.
The most plausible explanation to this seems to be a
dramatic decrease in the intra-intestinal methionine
tissue concentrations. Methionine is known to be the first
amino acid from which the protein synthesis starts from
] and the lack of “building blocks” would inevitably
decrease the intestinal cell wall renewal potential.
It is crucial to identify the specific mechanisms of the
paradoxical loss of the methionine tissue concentration.
To our knowledge, no studies reported this effect before.
For instance, Finkelstein and Martin reported that even
a 10-fold increase in the methionine dietary intake did
not affect the hepatic methionine concentrations during
the 7-day course of the study [
]. It must be noted that
although liver is primarily a mitotically dead organ in
which regeneration occurs only in the case of substantial
injury, the intestinal mucosa undergoes rapid
regeneration with a total cell wall renewal within the ~3.5 day
course. This predetermines very intense protein renewal.
Previous studies demonstrated that chronic
inflammatory diseases, infections, and nutritional status (including
particular amino acids) may significantly modulate
intestinal protein metabolism [
12, 13, 71, 74
]. The intestinal
inflammation and bacterial proliferation with an
abundance of pathogenic species observed in our study could
indeed lead to increased protein turnover. Another
possible explanation is the lack of methionine availability to
enterocytes. The latter primarily utilizes the apical
transport directly from the lumen . In these regards, the
amount of methionine available to enterocytes may be
substantially compromised: it might be either rapidly
captured by the boosting microbiome or swiftly
transported from the lumen into the blood paracellulary.
Future studies are clearly needed to confirm or rule out
these hypotheses. Furthermore, studies utilizing other
mouse strains will be needed to investigate the
genotype-dependent nature of methionine metabolism.
The effects caused by methionine dietary
supplementation may potentiate the effects of various exogenous
and endogenous stimuli. For instance, it has recently
been shown that excessive methionine dietary intake
potentiates ethanol-induced oxidative stress and
dyslipidemia in rats [
]. Another study demonstrated that even
moderate increases in methionine dietary intake are
atherogenic in susceptible mice [
]. Furthermore, to our
knowledge, no studies have investigated the effects of
methionine dietary intake in combination with
gastrointestinal injury inducers. Therefore, the effects of ionizing
radiation that causes substantial mucosal stem cell death,
leading to enterocyte depletion are particularly interesting
]. Further, bacterial infection is one of the leading
causes of death, as well as the major driver of the acute
radiation-induced gastrointestinal toxicity as a result of
accidental exposure or radiotherapy [
29, 38, 39, 58
these regards, the compromised gut with already affected
permeability, the abundance of pathogenic bacteria, and
depleted enterocyte mass may be predisposed to more
severe acute radiation toxicity. These studies are underway
in our laboratories and will be reported elsewhere.
Additional file 1: Gene expression and LINE-1 DNA methylation assays
used in the study. (DOCX 16 kb)
Additional file 2: Body weight dynamics of mice fed
methionineadequate (MAD) and methionine-supplemented (MSD) diets. (PDF 54 kb)
Additional file 3: Gut microbiome analysis in mice fed
methionineadequate and methionine-deficient diets. Principal Coordinates Analysis
based on unweighted Unifrac distances. (EPS 345 kb)
Additional file 4: Gut microbiome analysis in mice fed
methionineadequate and methionine-deficient diets, colored by group. A. Rarefaction
plot of species richness, subsampling from 500 to 20,000 reads in
increments of 500 reads. B. Chao1 richness within the total microbiome
data showing the mean value (and confidence interval) in each group.
C. Shannon diversity within the total microbiome data showing the mean
value (and confidence interval) in each group. (EPS 3776 kb)
LINE-1: Long interspersed nucleotide element 1; MAD: Methionine-adequate
diet; MSD: Methionine-supplemented diet; MYR: Million years; NFkB: Nuclear
factor kappa B; ORF: Open reading frame; OUT: Operational taxonomic unit;
qRT-PCR: Quantitative real-time polymerase chain reaction; rRNA: Ribosomal
RNA; SAH: S-adenosylhomocysteine; SAM: S-adenosylmethionine;
UTR: Untranslated region
The authors are thankful to Cellular and Molecular Analytic, and to Irradiation
and Animal Core Facilities within the COBRE under the grant number
1P20GM109005. The authors are thankful to Dr. Kristy Kutanzi for critical reading
and to Chris Fettes for editing the manuscript. The authors would like to thank
Dr. Ramesh Khanal (Envigo) for assistance with the animal diets preparation, to
Jennifer James of the UAMS Experimental Pathology Core Laboratory, and to Dr.
Christy Simecka, Bianca Schutte, and Erica Nicholson for providing excellent
animal care at the UAMS Animal Facility. This manuscript does not necessarily
reflect the views of the United States Food and Drug Administration.
Research reported in this publication was supported by an Institutional
Development Award (IDeA) from the National Institute of General Medical
Sciences of the National Institutes of Health under grant number
1P20GM109005; Clinical and Translational Science Awards UL1TR000039 and
KL2TR000063; the Arkansas Space Grant Consortium through National
Aeronautics and Space Administration grant NNX13AB29A; and the Arkansas
Availability of data and materials
The datasets supporting the conclusions of this article are included within
the article and its additional files.
IRM, RP, MH-J, and IK designed research. IRM, RP, SG, CMS, SM, OP, HH, and
IK conducted the research. IRM, SG, SM, HH, RL, AL, AJT, NEPD, MH-J, and IK
analyzed the data, and IK wrote the paper. All authors read and approved
the final manuscript.
This study was performed according to the principles and guidelines of the
National Institute of Health Guide for the Care and Use of Laboratory Animals.
All treatment and testing procedures were approved by the Animal Care and
Use Committee of the University of Arkansas for Medical Sciences, USA.
Consent for publication
The authors declare that they have no competing interests.
Springer Nature remains neutral with regard to jurisdictional claims in
published maps and institutional affiliations.
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