Access to this full-text is provided by Springer Nature.
Content available from Scientific Reports
This content is subject to copyright. Terms and conditions apply.
Scientic Reports | (2020) 10:21641 |
www.nature.com/scientificreports
The potential role of vitamin
D supplementation as a gut
microbiota modier in healthy
individuals
Parul Singh1, Arun Rawat1, Mariam Alwakeel2, Elham Sharif2* & Souhaila Al Khodor1*
Vitamin D deciency aects approximately 80% of individuals in some countries and has been linked
with gut dysbiosis and inammation. While the benets of vitamin D supplementation on the gut
microbiota have been studied in patients with chronic diseases, its eects on the microbiota of
otherwise healthy individuals is unclear. Moreover, whether eects on the microbiota can explain
some of the marked inter-individual variation in responsiveness to vitamin D supplementation is
unknown. Here, we administered vitamin D to 80 otherwise healthy vitamin D-decient women,
measuring serum 25(OH) D levels in blood and characterizing their gut microbiota pre- and post-
supplementation using 16S rRNA gene sequencing. Vitamin D supplementation signicantly
increased gut microbial diversity. Specically, the Bacteroidetes to Firmicutes ratio increased, along
with the abundance of the health-promoting probiotic taxa Akkermansia and Bidobacterium.
Signicant variations in the two-dominant genera, Bacteroides and Prevotella, indicated a variation in
enterotypes following supplementation. Comparing supplementation responders and non-responders
we found more pronounced changes in abundance of major phyla in responders, and a signicant
decrease in Bacteroides acidifaciens in non-responders. Altogether, our study highlights the positive
impact of vitamin D supplementation on the gut microbiota and the potential for the microbial gut
signature to aect vitamin D response.
Vitamin D is a lipid-soluble vitamin that is absorbed from dietary sources or supplements in the proximal small
intestine1, and is essential for maintaining skeletal integrity and function2, as well as for electrolyte reabsorption3,
and immune system regulation4. In some populations, sub-clinical vitamin D deciency is common, aecting
close to 40% of individuals in both the US5 and Europe6, as well as 80–85% of people living in Arab countries7–10.
is is of particular concern given recent studies revealing the association between vitamin D deciency and
a multitude of diseases including cancer, cardiovascular diseases11–13, diabetes, obesity14,15 and inammatory
bowel disease (IBD)16,17. In diabetes18 and IBD19, vitamin D is intimately involved in the regulation of inamma-
tion via a bidirectional relationship with the gut microbiota20,21. Studies also suggest that the amount of dietary
vitamin D and its circulating levels may be involved in maintaining immune homeostasis in healthy individuals,
partially via modulating the gut microbial composition22. However, it is currently unknown how supplementing
otherwise-healthy vitamin D-decient people aects their gut microbiota.
Several studies have assessed the impact of vitamin D supplementation on the microbiota composition, pre-
dominantly in disease states. For example, Kanhere etal. showed that weekly vitamin D supplementation modies
the gut and airway microbiota in patients with cystic brosis23. In another study, vitamin D3 supplementation
of patients with multiple sclerosis increased abundance of the mucosal-integrity-promoting genus Akkermansia
in the gut, as well as Fecalibacterium and Coprococcus; these latter two being the major butyrate producers of
the Firmicutes phylum24. Similarly, in vitamin D-decient pre-diabetic individuals, supplementation leading to
increased serum 25(OH) D was inversely correlated with abundance of Firmicutes (genus Ruminococcus) and
Proteobacteria, and positively correlated with Bacteroidetes abundance22,25,26. A randomized clinical trial in vita-
min D-decient overweight or obese adults also showed that increased levels of vitamin D were associated with
greater abundance of bacteria from the genus Coprococcus and lower abundance of the genus Ruminococcus27.
Studies examining the eect of vitamin D supplementation on the gut microbiota composition of healthy
individuals are limited. In one study, increased relative abundance of Bacteroidetes and decreased Proteobacteria
OPEN
Research Department, Sidra Medicine, Doha, Qatar. College of Health Sciences, Qatar University, Doha,
Qatar. *email: e.sharif@qu.edu.qa; salkhodor@sidra.org
Content courtesy of Springer Nature, terms of use apply. Rights reserved
Vol:.(1234567890)
Scientic Reports | (2020) 10:21641 |
www.nature.com/scientificreports/
was reported, but only in biopsies from the upper gastrointestinal tract and not in fecal samples28. However, a
small study with twenty healthy Vitamin D-decient/insucient subjects showed a signicant dose-dependent
increase in the relative abundance of Bacteroides and Akkermansia spp, coupled with a decrease in Firmicutes-to-
Bacteroidetes ratio and decreased relative abundance of Fecalibacterium spp. and the Ruminococcaceae family29.
us, there is some controversy around the eects of vitamin D supplementation of healthy individuals on the gut
microbiota and whether these eects are signicant in the lower gastrointestinal tract of a large study population.
Further complicating our understanding of the impact of vitamin D deciency and the eects of supple-
mentation is the observation that changes in serum levels of the vitamin D pre-hormone metabolite, 25(OH)D
(25-hydroxyvitamin D), post-supplementation vary widely among individuals30–33, with around 25% of people
demonstrating little or no increase in blood 25(OH)D following vitamin D2/D3 supplementation34. A systematic
review by Zittermann etal. concluded that individual variations in serum 25(OH) D levels post supplementation
could be partly explained by dierences in dose per kg of body weight (34.5%), the type of supplement used (D2 or
D3, 9.8%), age (3.7%), concurrent calcium supplementation (2.4%) and baseline 25(OH)D concentration (1.9%)35;
however, this leaves 50% of the inter-individual dierence in response unaccounted for. Given the evidenced
bi-directional interaction between vitamin D and the gut microbiota in inammation, we hypothesized that the
composition of the gut microbiota might also aect responsiveness to vitamin D intake.
erefore, in this study we characterized the composition and diversity of the gut microbiota in a group of
healthy adult females before and aer supplementation with vitamin D, and established both the eects of sup-
plementation on gut microbiota and whether specic microbial signatures were associated with the dierential
serum response to oral vitamin D supplements.
Results
Participant characteristics and the eects of vitamin D supplementation on blood biochemis-
try. We enrolled 100 healthy female subjects into the study, of which 80 successfully completed the two phases
(phase I-baseline-pre-supplementation; phase II- post-supplementationwith vitamin D3). e study workow
and exclusion criteria are shown in (Fig.1A). Briey, following enrollment, blood and stool samples were col-
lected; all participants were then given a weekly oral dose of 50,000IU vitamin D3 to be taken for the following
12weeks, at which time a second set of blood and stool samples were taken, the phaseIand phase II samples
were analyzed for serum 25(OH) and gut microbiota composition. Baseline clinical and demographic character-
istics of the participants are summarized in (Table1). Briey, the mean age of the cohort was 21years, and 87%
of the participants were Arabs. e average body mass index (BMI) of the subjects was 24.39 ± 0.530kg/m2, with
the majority of individuals falling into the normal weight category.
At the start of the study, participants had 25(OH)D levels classed as either decient (less than 20ng/ml, 96%
of all participants) or insucient (less than 30ng/ml, 4% of the remaining participants) according to published
limits36. is is consistent with the most recent Qatar Biobank report showing over 88% of the population has
inadequate levels of vitamin D10. Aer 12weeks of vitamin D supplementation in the absence of signicant self-
reported dietary change, we found that average serum 25(OH) D levels had increased signicantly across the
group (baseline 11.03 ± 0.51ng/ml to post-supplementation 34.37 ± 1.47ng/ml (p = 5.1e−14; paired Wilcoxon,
Fig.1B). Overall, 89% of participants achieved a serum level of 25(OH)D > 20ng/ml, with 69% reaching a
sucient level exceeding 30ng/ml (data not shown). e 11% of subjects that remained decient (< 20ng/ml
25(OH)D) in vitamin D despite supplementation were classied as non-responders37,38. As expected, we also
found that average calcium concentration increased signicantly post-vitamin D supplementation (Table1 and
Supplementary Fig.S1A).
As vitamin D deciency is associated with chronic liver39 and kidney40 diseases, we also measured markers of
the function of these organs. We found that vitamin D supplementation signicantly decreased the ratio of serum
blood-urea-nitrogen (BUN)/Creatinine, indicating improved kidney function, as well as decreasing the ratio
of aspartate aminotransferase (AST)/ alanine aminotransferase (ALT), indicative of improved liver functioning
(Table1 and Supplementary Fig.S1B/C). ese results are consistent with a study showing that kidney function
(BUN/Creatinine ratio) improved in vitamin D-decient patients who took vitamin D supplements than those
that didn’t41. Similarly, a cross sectional study of 5528 school students found that abnormal liver function tests
were corrected (the AST/ALT ratio was decreased) post vitamin D supplementation42. Taken together, we show
that weekly oral supplementation of vitamin D in healthy females was eective in restoring healthy levels of blood
25(OH)D in majority of the participants. Moreover, this increase was associated with increased blood calcium
levels and improvements to blood markers of kidney and liver function in this cohort.
Eects of vitamin D supplementation on gut microbiota composition. We next determined the
bacterial composition of stool samples from participants before and aer 12weeks of vitamin D supplementa-
tion using 16S rRNA gene sequencing on the Illumina MiSeq platform. We generated 9.4 million (9,405,441)
paired-end sequences of the 16S rRNA genes from the 80 subjects providing samples pre- and post- supple-
mentation. e mean number of sequences was 58,784 ± 31,109 per sample. Aer de-noising, we dened 7,332
operational taxonomic units (OTUs), with a mean length of 411.5 ± 19.19bp. ese OTUs were classied into 12
dierent phyla, as shown in the prevalence plot in (Supplementary Fig.S2).
e adult human gut is generally predominantly populated by bacteria within the phyla Bacteroidetes and
Firmicutes43; as well as the less abundant Actinobacteria, Proteobacteria, and Verrucomicrobia44. Accordingly,
here we found that, pre-supplementation, Firmicutes and Bacteroidetes represented around 95% of the total
sequencing reads: the mean relative abundance of Firmicutes (55.86%) and Bacteroidetes (40.70%) were by far
the highest across all the samples we analyzed, followed by Actinobacteria (2.00%), Proteobacteria (1.15%) and
Verrucomicrobia (0.21%) (Fig.1C). However, following vitamin D supplementation, the mean relative abundance
Content courtesy of Springer Nature, terms of use apply. Rights reserved
Vol.:(0123456789)
Scientic Reports | (2020) 10:21641 |
www.nature.com/scientificreports/
Figure1. e schematic representation of study design and analysis. (A) Flow chart of subject selection along
with inclusion/exclusion criteria. (B) Changes in serum levels of vitamin D(ng/ml) in study subjects pre- and
post- supplementation. Microbiota composition in stool samples pre- and post- vitamin D supplementation. (C)
e relative abundance of bacterial phyla: Firmicutes and Bacteroidetes were signicantly impacted post Vitamin
D (Wilcoxon test with false discovery rate (FDR)-Bonferroni corrected ****P < 0.0001 and *P < 0.05 respectively)
(D) Comparison of the ratio of Bacteroidetes to Firmicutes pre- and post- vitamin D supplementation (Lmer4
borderline signicant p = 0.0579) cumulative and per subject level. e gure was generated using (RStudio v 1.2
with R v 3.6)87.
Content courtesy of Springer Nature, terms of use apply. Rights reserved
Vol:.(1234567890)
Scientic Reports | (2020) 10:21641 |
www.nature.com/scientificreports/
of Firmicutes decreased signicantly to 50.57% (p < 2.2e−16), while the mean relative abundance of Bacteroidetes
increased signicantly to 43.62% (p = 0.001) (Fig.1C). Using a mixed model with repeated measures (lme4)45 we
conrmed that the 12week supplementation with vitamin D impacted the Bacteroidetes/Firmicutes (B/F) ratio.
Our data showed that the B/F ratio was higher post vitamin D supplementation (0.818 ± 0.048 vs. 0.954 ± 0.061;
p = 0.0579) (Fig.1D). Among other phyla, the relative abundance of Actinobacteria (pre-1.9% vs post- 3.1%) and
Verrucomicrobia (pre-0.19% vs post-0.95%) also increased (Fig.1C).
At the genus level, pair-wise comparison of the top 10 most abundant genera from each phylum revealed
signicant increases in the relative abundance of Bidobacterium (predominant genus in Actinobacteria) and
Akkermansia (only known member of phylum Verrucomicrobia) following vitamin D supplementation (p = 0.018)
(Fig.2A, Supplementary Fig.S3). In contrast, the abundance of several core genera in the phylum Firmicutes,
such as Roseburia, Ruminococcus, and Fecalibacterium decreased post supplementation (Supplementary Figs.S4
and S6); whereas members of the phylum Bacteroidetes showed an increase in relative abundance of the genera
Bacteroides, Alistipes and Parabacteroides, and a decrease in Prevotella (Supplementary Figs.S5 and S6). e
change in the relative abundance of the two dominant genera within Bacteroidetes, Bacteroides and Prevotella
(marked by a signicant increase in the Bacteroides/Prevotella ratio, p = 0.0057) (Fig.2B) combined with the
decreased abundance of Ruminoccoccus indicates a shi of enterotypes in favour of the Bacteroides-dominated
enterotype (ET B)43. Altogether the results indicate that vitamin D supplementation results in alteration of the
composition of both the major and minor phyla in the gut of healthy individuals.
Eects of vitamin D supplementation on richness and diversity of the gut microbiota. In
contrast to previous studies, we found a signicant impact of vitamin D supplementation on both alpha and
beta diversity of the gut microbiota in healthy females. At the end of the 12week supplementation period, we
observed a statistically signicant increase in the observed OTUs (p = 1.6e−05) and Chao1 indices (p = 1.1e−05),
whereas the Shannon and InvSimpson indices were not signicantly dierent (p = 0.71 and p = 0.27 respectively)
(Fig.3A). When we evaluated the overall structure of the fecal microbiota using β diversity indices, we found
a signicant dierence in the weighted UniFrac dissimilarity matrix between the two groups (PERMANOVA
p = 0.048) (Fig.3B).
Table 1. Baseline Characteristics of Study Participants. SEM, Standard error of measurement; BMI, Body
massindex; BUN, blood urea nitrogen; ALT, alanine aminotransferase; AST, aspartate aminotransferase.
Characteristic Measure
Age, mean (range in years) 21(17–28)
Ethnicity, n (%)
Arab 70 (87.5%)
Non- Arab 10 (12.5%)
BMI, mean ± SEM 24.39 ± 0.530
Classication according to BMI
Underweight, n (%) 4 (5%)
Normal weight, n (%) 52 (65%)
Overweight, n (%) 14 (17.5%)
Obese, n (%) 10 (12.5%)
Average Daily Exposure to Sun
Less than 1/2h, n (%) 30 (37.5%)
1/2h to 1hr, n (%) 32 (40%)
more than 1h, n (%) 18 (22.5)
Frequency of sh consumption
Daily, n (%) 0 (0%)
Weekly, n (%) 16 (20%)
Monthly, n (%) 40 (50%)
None, n (%) 24 (30%)
History of Vitamin D deciency
Yes (%) 76%
No (%) 24%
Biochemical parameters Pre Post
Serum 25(OH)D level, ng/ml, means ± SEM 11.03 ± 0.521 34.37 ± 1.476
Calcium(mg/dl), means ± SEM 9.18 ± 0.146 11.34 ± 0.165
Creatinine(mg/dl), means ± SEM 0.46 ± 0.013 0.677 ± 0.017
BUN (mg/dl), means ± SEM 9.81 ± 0.318 12.61 ± 0.393
ALT(U/L), means ± SEM 9.86 ± 0.521 13.01 ± 0.721
AST(U/L), means ± SEM 15.14 ± 0.558 16.46 ± 0.613
Content courtesy of Springer Nature, terms of use apply. Rights reserved
Vol.:(0123456789)
Scientic Reports | (2020) 10:21641 |
www.nature.com/scientificreports/
us, the above results suggest the diversication of gut microbiota in healthy adult females post vitamin D
Figure2. Changes in relative abundance of specic bacterial genera in stool samples pre- and post- vitamin
D supplementation. (A) Relative abundance of genus Akkermansia (Wilcoxon test with false discovery rate
(FDR)-corrected pairwisePvalues. *P < 0.05) (B) Comparison of the ratio of Bacteroides to Prevotella pre- and
post- supplementation; (Wilcoxon test with false discovery rate (FDR)-Bonferroni corrected pairwisePvalues.
*P < 0.05) e gure was generated using (RStudio v 1.2 with R v 3.6)87.
Figure3. Diversity of microbiota composition in stool samples pre- and post- vitamin D supplementation. (A)
Boxplots of Alpha-diversity indices: Observed OTUs; Chao1; Shannon and Inverse Simpson. Boxes represent
the interquartile range (IQR) between the rst and third quartiles (25th and 75th percentiles, respectively), and
the horizontal line inside the box denes the median. Whiskers represent the lowest and highest values within
1.5 times the IQR from the rst and third quartiles, respectively. Statistical signicance was identied by the
Wilcoxon test with false discovery rate (FDR)-Bonferroni corrected pairwise P values. *P < 0.05; **P < 0.01;
***P < 0.001 and ****P < 0.0001. (B) PCA on a weighted UniFrac dissimilarity matrix shows signicant
dierences in β diversity of bacterial populations pre- and post- vitamin D supplementation, with higher
variance post supplementation. *P < 0.05) e gure was generated using (RStudio v 1.2 with R v 3.6)87.
Content courtesy of Springer Nature, terms of use apply. Rights reserved
Vol:.(1234567890)
Scientic Reports | (2020) 10:21641 |
www.nature.com/scientificreports/
supplementation.
Association of microbial signatures with response to vitamin D supplementation. Studies
show a high interpersonal variability in the response to vitamin D supplementation, the reasons for which are
incompletely understood. Given the bi-directional relationship between vitamin D and the microbiota in inam-
mation, we hypothesized that a similar interaction might occur in determining responsiveness to vitamin D sup-
plementation. We thus categorized our subjects as responders or non-responders based on their vitamin D levels
post supplementation: responders were dened as those who achieved serum levels of 25(OH) D above 20ng/
ml and the non-responders were those whose serum levels of 25(OH) D remained < 20ng/ml) (Fig.4A)37,38.
We next asked whether the two groups diered with respect to changes in gut microbial composition during
supplementation. e two groups ordinated based on their treatment status (pre/post supplementation; PER-
MANOVA p = 0.048) (Supplementary Fig.S7); as well as segregating into responders and non-responders, based
on the variation in the microbiota composition as a result of vitamin D supplementation. Vitamin D responders
showed signicant increases in the relative abundance of Bacteroidetes(p = 0.012), Actinobacteria (p = 0.010),
Proteobacteria (p = 0.005) and Lentisphaeraea (p = 0.05), coupled with decreased abundance of Firmicutes
Figure4. Comparison of changes in serum vitamin D levels (ng/ml) and gut microbiota composition in
responders and non-responders to vitamin D supplementation. (A) Serum vitamin D levels pre- and post-
supplementation in responders and non-responders. (B) Relative abundance of dierent bacterial phyla pre and
post supplementation in responder and non-responder groups. (C) e ratio of Bacteroidetes to Firmicutes in
responders and non-responders, pre- and post- vitamin D supplementation. e gure were generated using
(RStudio v 1.2 with R v 3.6)87.
Content courtesy of Springer Nature, terms of use apply. Rights reserved
Vol.:(0123456789)
Scientic Reports | (2020) 10:21641 |
www.nature.com/scientificreports/
(p < 2.2e−16) at the phylum level post supplementation (Fig.4B); In non-responders changes were observed in
the abundance of Proteobacteria(p = 0.02). Vitamin D responders also showed a greater increase in the B/F ratio
post-supplementation, compared to non-responders (Fig.4B). At the species level, we performed a dierential
abundance analysis using DESeq2 to compare responders and non-responders pre and post-vitamin D sup-
plementation. Several microbes including Bacteroides acidifaciens, Ruminococcus bromii, Bacteroides eggerthii,
Barnesiella intestinihominis were found to be signicantly enriched in responders compared to non-responders
both in pre and post-supplementation (padj < 0.05) (Supplementary Fig.S8A/B), suggesting that the enrichment
with these microbes may be associated with the response to vitamin D supplementation. We next asked the ques-
tion, which among these species were further depleted specically in non-responders post-supplementation.
Our analysis revealed a signicant depletion of B. acidifaciens compared to other species in non-responders post
supplementation (padj < 0.05) (Fig.5A), which was also conrmed by Wilcoxon paired test (Fig.5B/C). ese
results suggest that lower baseline levels of B. acidifaciens prior to vitamin D supplementation, combined with
its continued depletion post supplementation may be indicative of poor response to vitamin D.
Both responders and non-responders showed an increase in alpha diversity post supplementation, as per
the Observed and Chao 1 indices (data not shown). Collectively the signatures revealed that vitamin D sup-
plementation has a dierential modulatory eect on the microbial composition of the gut in responders and
non-responders. While both groups exhibit changes in microbial composition and diversity following supple-
mentation, the specics of this change vary dependent on response status.
Predicted functional proling of the gut microbial communities pre- and post- vitamin D sup-
plementation. To predict the functional role of the microbial communities identied, we used PICRUSt
analysis46. Our data revealed marked dierences between predicted patterns of functional genes pre- and post-
vitamin D supplementation (Supplementary Fig.S9). Importantly, we saw signicant dierences in genes related
to host-symbiont metabolic pathways, including folate biosynthesis, and glycine, serine and threonine metabo-
lism pre- and post- supplementation (Fig.6A/B). Several strains of Bidobacterium are able to produce folate47,48,
thus this increase in the abundance of this genus may explain the predicted increase of folate biosynthesis.
Moreover, the predicted increase in the bacterial glycine metabolism genes is potentially important, as lower
plasma levels of glycine have been linked with obesity and type 2 diabetes49; bacterial glycine metabolism can
Figure5. Species level comparison within gut microbiota of responders and non-responders to vitamin
D supplementation. (A) DESeq2 dierential abundance analysis of signicantly dierent OTUs post/pre in
non-responders (p < 0.05, FDR-corrected); OTUs to the right of the zero line were more abundant in non-
responders post- supplementation and OTUs to the le of the zero line were less abundant. (B–C) Comparison
of relative abundance of B. acidifaciens in non-responders (B) and responders (C) pre- and post-vitamin D
supplementation. Signicant decrease in non-responders post supplementation (**P < 0.01). Responders show
non-signicant change. Statistical signicance was identied by the Wilcoxon test with false discovery rate
(FDR)-Bonferroni corrected pairwisePvalues. *P < 0.05; **P < 0.01). e gure was generated using (RStudio v
1.2 with R v 3.6)87.
Content courtesy of Springer Nature, terms of use apply. Rights reserved
Vol:.(1234567890)
Scientic Reports | (2020) 10:21641 |
www.nature.com/scientificreports/
vary with changes in microbiota composition and richness50, as seen in this study. Our analysis also predicted an
increased in genes related to several pathways involved in lipid metabolism, fatty acid biosynthesis and metabo-
lism of cofactors and vitamins post-vitamin D supplementation(Fig.6C); this is particularly interesting because
of the vital role of lipids and fatty acids in the absorption of vitamin D (fat soluble) in the intestinal lumen.
Discussion
In this study we aimed to characterize changes in the gut microbiota of vitamin D-decient female volunteers
following 12weeks of vitamin D supplementation. In addition, we wanted to assess whether any characteristics
of the gut microbiota were linked with the response to vitamin D supplementation. We found that vitamin D
supplementation increased the overall diversity of the gut microbiota, and in particular the increased the relative
abundance of Bacteroidetes and decreased the relative abundance of Firmicutes. A high ratio of Firmicutes to
Bacteroidetes has been correlated with obesity51 and other diseases52–54; while conversely a prebiotic interven-
tion that decreased the Firmicutes to Bacteroidetes ratio resulted in improvements to gut permeability, metabolic
endotoxemia and inammation55. Alongside the results of a recent pilot study29, our data solidify the proposed
link between Vitamin D supplementation and decreased Firmicutes to Bacteroidetes ratio, which is associated
with improved gut health54.
In addition to improving the Bacteroidetes to Firmicutes ratio, our data show that members of Verrucomicro-
bia and Actinobacteria phyla also increased in abundance following vitamin D supplementation. Akkermansia
muciniphila is the only representative of the phylum Verrucomicrobia in the human gut,56,57 and helps maintain
host intestinal homeostasis by converting mucin into benecial by‐products58. e abundance of A. muciniphila
Figure6. Inferred gut microbiome functions by PICRUSt from 16S rRNA gene sequences pre- and post-
vitamin D supplementation. Dierence in predicted functions of genes involved in (A) biosynthesis of
folate; and (B) glycine, serine and threonine metabolism (C) biosynthesis of unsaturated fatty acids (Mann–
Whitney*P < 0.05;). e gure was generated using (RStudio v 1.2 with R v 3.6)87.
Content courtesy of Springer Nature, terms of use apply. Rights reserved
Vol.:(0123456789)
Scientic Reports | (2020) 10:21641 |
www.nature.com/scientificreports/
negatively correlates with body mass59,60 inammation61 metabolic syndrome62 and both type 1 and type 2
diabetes60,63. Our analysis also showed a signicant increase in the abundance of Bidobacterium which is an
important probiotic with a wide array of benets to human health64, as well as playing a role in folate and amino
acid production65. Accordingly, using PICRUSt predictive functional analysis, we predicted an increased in genes
involved in folate production and biosynthesis of several amino acids following vitamin D supplementation.
Alongside characterising individual taxa, Wu etal. clustered fecal communities into two enterotypes distin-
guished primarily by the levels of Bacteroides and Prevotella, and found that vitamin D intake was negatively
associated with abundance of the Prevotella enterotype, instead being strongly positively associated with the
Bacteroides enterotype66. In line with this, we found that vitamin D supplementation favoured a Bacteroides-
dominated enterotype over Prevotella. is is potentially important as several studies indicate Prevotella as an
intestinal pathobiont: high levels of Prevotella spp. have been reported in children diagnosed with irritable bowel
syndrome67; while the expansion of Prevotella copri was strongly correlated with enhanced susceptibility to
arthritis68.Taken together, our results make a compelling argument that vitamin D supplementation modulates
the gut microbiota composition and diversity towards a more benecial state—a previously undescribed benet
of vitamin D.
At present, the mechanism underlying vitamin D regulation of the gut microbiota is not clear. One possibility
is that, following absorption in the small intestine1, vitamin D could impact gut microbial communities via indi-
rect systemic mechanisms; for example, the vitamin D receptor (VDR) is highly expressed in the proximal colon
and acts as a transcription factor regulating expression of over 1000 host genes involved in intestinal homeo-
stasis and inammation, tight junctions, pathogen invasion, commensal bacterial colonization, and mucosal
defense70, including the defensins, cathelicidin, claudins, TLR2, zonulin occludens, and NOD269,70. Interestingly,
there is some recent evidence of the cross talk between the gut microbiota and VDR signalling aecting host
responses and inammation, and this appears to be bidirectional9. Intestinal VDR expression has been shown
to regulates the host microbiota to mediates the benecial eects of probiotics71,72 and vitamin D treatment72–75.
Similarly, probiotics and pathogenic bacteria have been also shown to modulate VDR expression, with the former
increasing76, and the latter decreasing77, its expression.
Alternatively, or alongside such systemic mechanisms, growing evidence suggests that vitamins administered
in large doses escape complete absorption by the proximal intestine78, and so might then be available to directly
modulate the distal gut microbiome. Whether this is the case for the vitamin D remains to be investigated; how-
ever, such a mechanism might account for the dierences in microbiota change seen in various studies employing
high versus low dose supplementation protocols.
Interestingly, in our study microbial functional potentials inferred using PICRUSt indicated that vitamin
D supplementation elevated pathways associated with the metabolism of amino acids, cofactors, vitamins, and
lipids, including steroid biosynthesis and fatty acid elongation. is could be important as adequate concen-
trations of lipids, bile salts and fatty acids are required for incorporation of fat-soluble vitamin D into mixed
micelles, as a prerequisite for its absorption79,80. us, increased abundance of bacterial genes related to lipid and
fatty acid metabolism post supplementation could indicate increased vitamin D bioavailability and absorption
in the gut81.
While the benets of vitamin D supplementation in decient/insucient level individuals are clear, there are
a sub-group of people in which even high-dose oral vitamin D supplementation has been shown to be ineective.
A secondary aim of this study was to assess whether the microbiota in these individuals could be associated with
their non-responder status. Lower levels of baseline Bacteroides acidifaciens in non-responders combined with an
additional depletion post-supplementation suggest that this bacterium may be linked with response to vitamin
D supplementation. Bacteroides acidifaciens has previously been proposed as a “lean bug” that could prevent
obesity and improve insulin sensitivity82. It is also one of the predominant commensal bacteria that promote IgA
antibody production in the large intestine. us, we hypothesize that the vitamin D supplementation promotes
the ‘farming’ of good bacteria in order to maintain immune–microbe homeostasis.
While results from this study are promising and warrant more research, it is worth noting that our study has
few limitations. Firstly, we did not have vitamin D sucient controls to observe the impact of vitamin D supple-
mentation in comparison with the decient subjects. Secondly, addition of a placebo group would minimize the
potential eects of non-treatment factors. Lastly, experimental studies with larger cohort needs to be undertaken
to have sucient representation of study responders/non-responders to conrm the nding of the present study.
In conclusion, vitamin D supplementation of decient/insucient otherwise healthy females changed the
composition and diversity of the gut microbiota, eliciting a benecial eect by improving health-promoting taxa
along with clinical biomarkers for kidney and liver function. Our study also provides a proof-of-concept that the
gut microbiota is informative in examining individualized responses to vitamin D supplementation, presenting
a rationale for planning future clinical trials that focus on the inter and intra individual variation using multi-
omics approaches such as genotyping, transcriptomics and proteomics.
Methods
Study participants and design. e study was approved by Qatar University (QU) Institutional Review
Board (IRB) (QU-IRB; 531-A/15) and by Sidra Medicine IRB (1,705,010,938). e Investigators ensured that
the study was conducted in full conformity with the current revision of the Declaration of Helsinki and with the
ICH Guidelines for Good Clinical Practice (CPMP/ICH/135/95) July 1996. One hundred female students from
QU were recruited for the study starting March 2018. Follow-up for the last subject was completed in September
2018. All subjects enrolled were healthy and did not have any underlying diseases or conditions. Subjects were
excluded if they were taking vitamin D, antibiotics or were suering from any chronic disease. Subjects were
Content courtesy of Springer Nature, terms of use apply. Rights reserved
Vol:.(1234567890)
Scientic Reports | (2020) 10:21641 |
www.nature.com/scientificreports/
excluded from the nal analysis if they failed to provide the blood or stool sample at either pre- or post- sup-
plementation sampling points.
A total of 80 subjects were enrolled in the study aer considering all the inclusion and exclusion criteria
(Fig.1A). Participants received the explanation about study aims and procedures before starting the interven-
tion. All individuals were asked to complete a questionnaire that included present and past medical history,
supplementation, dietary habits, exposure to sunlight and other details for the study. All participants underwent
a physical examination and submitted their informed consent before inclusion. Aer the baseline assessment,
blood and stool samples were collected and each participant received a weekly oral dose of 50,000IU vitamin D3
(Nivagen pharmaceuticals, USA) to be taken for 12weeks (phase I-baseline-pre-supplementation with vitamin
D3). To encourage compliance, subjects were notied via phone messages to take their pills each week and were
tested based on the pill count at the 12weeks follow-up visit, where blood and stool samples were collected again
(phase II- post-supplementation). Participants were asked to maintain their regular diet and eating practices.
Intake of dairy products (milk, cheese, yogurt and butter/margarine) and sh was recorded for each participant
as these are considered possible confounders of dietary vitamin D level.
At the end of the intervention, participants were classied as either responders to vitamin D supplementation
(those who achieved serum levels of 25(OH) D above 20ng/ml) or non-responders (those whose serum levels
of 25(OH) D remained < 20ng/ml)37,38.
Sample collection and biochemical measures. Around 4ml of peripheral blood was collected aer
overnight fasting from each participant in phase I (baseline-pre-supplementation) and in phase II (post-supple-
mentation). Whole blood samples were centrifuged and separated within 3h of venipuncture, and serum por-
tions were frozen at − 80°C for future measurement of creatinine, calcium, blood urea nitrogen (BUN), aspartate
aminotransferase (AST), alanine aminotransferase (ALT), and 25-hydroxyvitamin [25(OH)D] levels. ALT, AST,
BUN, calcium and creatinine were measured using EasyRA analyzer and 25-hydroxyvitamin [25(OH)D] was
measured using the DIAsource 25OH vitamin D Total ELISA 90′ Kit (catalog number: KAP1971/F1).
Microbial DNA extraction from stool samples. A fraction of the collected stool sample (400–500mg)
was transferred to the OMNIgene GUT kit (DNA Genotek Inc, Ottawa, Canada), according to the manufac-
turer’s protocol. QIAamp Fast DNA Stool Mini Kit was used for fecal DNA extraction according to the manu-
facturer’s protocols. e DNA concentration and purity were evaluated using a Nanodrop spectrophotometer
(ermo Scientic, Wilmington, DE, USA). e extracted DNA samples were stored at − 20°C until library
preparation.
DNA sequencing and gut microbial proling. PCR amplication and high throughput sequencing. e
16S rRNA variable regions V3 and V4 were amplied with polymerase chain reaction (PCR), using the Illumina
recommended amplicon primers:
Forward: 5′TCG TCG GCA GCG TCA GAT GTG TAT AAG AGA CAG CCT ACG GGNGGC WGC AG;
Reverse: 5GTC TCG TGG GCT CGG AGA TGT GTA TAA GAG ACAG GAC TAC HVGGG TAT CTA ATC C.
e PCR mixture comprised 5μl of each forward and reverse primer (1μM), 2.5μl of template DNA for
the samples, and 12.5μl of 1× Hot Master Mix (Phusion Hot start Master Mix) to a nal volume of 25μl. e
amplications were performed under the following conditions: initial denaturation at 95°C for 2min, followed
by 30 cycles of denaturation at 95°C for 30s, primer annealing at 60°C for 30s, and extension at 72°C for 30s,
with a nal elongation at 72°C for 5min. e presence of PCR products was visualized by electrophoresis using a
1.5% agarose gel. All amplicons were cleaned and sequenced according to the Illumina MiSeq 16S Metagenomic
Sequencing Library Preparation protocol (http://suppo rt.illum ina.com/downl oads/16s_metag enomi c_seque
ncing _libra ry_prepa ratio n.html). Samples were multiplexed using a dual-index approach with the Nextera XT
Index kit (Illumina, San Diego, USA) according to the manufacturer’s instructions. Amplicon library concentra-
tions were determined using the Qubit HS dsDNA assay kit (Life Technologies, Australia). e nal library was
paired end sequenced at 2 × 300bp using a MiSeq Reagent Kit v3 on Illumina MiSeq platform (Illumina, San
Diego, USA), at the Sidra research facility.
16S sequence data processing and statistical analysis. e sequencing quality was evaluated using Fast QC
[http://www.bioin forma tics.babra ham.ac.uk/proje cts/fastq c] and the demultiplexed sequencing data imported
into Quantitative Insights into Microbial Ecology (QIIME2; version 2019.4.0) soware package83,84 [https ://
qiime 2.org/]. Although the overall distribution was uniform across pre- and post- supplementation samples
(Supplementary Fig.S10), several samples such as 33, 70 and 74 exhibited unequal distribution. e data were
normalized to overcome the inherent bias in amplicon sequencing, as discussed below. e rarefaction curves
tapered phylogenetically as the sequencing depth increased, implying that the entire microbial population was
suciently represented (Supplementary Figs.S11 and S12) and the samples were rareed at a depth of > 10,000.
Samples from subjects 33, 70 and 74 were removed from the nal analysis because of low sampling depth and
the skewed distribution noted above. e data were denoised with DADA285—this multiple step process runs
from read ltering to dereplication to chimera removal. Both paired reads were trimmed from the forward end
and read length of at least 250bp for further processing to generate the amplicon sequence variant (ASV), or
interchangeably called operational taxonomic units (OTUs). Taxonomic classication was performed utilizing
16S rRNA gene database from Greengenes (http://green genes .lbl.gov)86 (version 13_8). e OTUs were classi-
ed using QIIME2 and the data imported into R (RStudio v 1.2 with R v 3.6)87 in a Biological Observation Matrix
(biom) format, before further evaluation with the Phyloseq package88 among others. e nal set of ASVs/
OTUs was nally utilized for taxonomical classication using a pre-trained classier (trained at 99% OTU full-
Content courtesy of Springer Nature, terms of use apply. Rights reserved
Vol.:(0123456789)
Scientic Reports | (2020) 10:21641 |
www.nature.com/scientificreports/
length sequences) against Greengenes database 13_8 as provided by Qiime283,84. For normalization, we utilized
a random subsampling or the rarefaction on OTUs count. We also performed nonparametric statistical testing
utilizing two-tailed Wilcoxon signed rank test for paired analysis89, and calculated the false discovery rate (FDR)
with Bonferroni correction and resulting p value < 0.05 considered signicant for all tests.
Alpha Diversity (within sample community) was assessed by observed OTUs (i.e., sum of unique OTUs
per sample), Chao190 (abundance based richness estimators, which is sensitive to rare OTUs), Shannon91 and
inverse Simpson (InvSimpson)92 (which is more dependent on highly abundant OTUs and less sensitive to rare
OTUs) indices in RStudio using the R package “vegan” (v2.5–6)93. Beta Diversity (Divergence in community
composition between samples) was assessed using four dierent distance metrics: Weighted Unifrac, Unweighted
Unifrac, Bray–Curtis (abundance) and Jaccard. PCA was used as an ordination method and signicance was
determined using the Adonis test (PERMANOVA) which considers the multidimensional structure of the data
(e.g., compares entire microbial communities) to determine the signicance (999 permutations). e B/F ratio
was calculated with a mixed model for repeated measures controlling for random subject-specic eects with
the LME4 package94.
Metagenome functional contents were analyzed using the PICRUSt soware package (v1.0.0) to predict
gene contents and metagenomic functional information46. e statistical evaluation was then performed with
STAMP95 and signicant pathways (p value < 0.05, CI 99%) were exported and used to generate the heatmap
shown in (Supplementary Fig.S8).
To delineate the dierentially abundant bacterial taxa in responders/non-responders to vitamin D supple-
mentation we used DESeq296. In the dierential abundance analysis, rarefaction may lead to a lower power97;
thus DESeq2 analysis was carried out on the un-rareed data to allow maximum participation of sequenced
reads (taking the entire data into consideration) using the DESeq2 inbuilt library size normalization facility.
Ethics approval and consent to participate/publish. e study was approved by Qatar Univer-
sity (QU) Institutional Review Board (IRB) (QU-IRB; 531-A/15) and by Sidra Medicine IRB (1705010938).
Informed consent to participate in and publish the study was obtained from all the participants and/or their
legal guardians.
Data availability
e data is available upon request.
Received: 27 March 2020; Accepted: 13 November 2020
References
1. Hollander, D. & Truscott, T. C. Mechanism and site of small intestinal uptake of vitamin D3 in pharmacological concentrations.
Am. J. Clin. Nutr. 29, 970–975. https ://doi.org/10.1093/ajcn/29.9.970 (1976).
2. B ell, T. D., Demay, M. B. & Burnett-Bowie, S.-A.M. e biology and pathology of vitamin D control in bone. J. Cell. Biochem. 111,
7–13. https ://doi.org/10.1002/jcb.22661 (2010).
3. Friedman, P. A. & Gesek, F. A. Cellular calcium transport in renal epithelia: Measurement, mechanisms, and regulation. Physiol.
Rev. 75, 429–471. https ://doi.org/10.1152/physr ev.1995.75.3.429 (1995).
4. Aranow, C. Vitamin D and the immune system. J. Investig. Med. 59, 881–886. https ://doi.org/10.2310/JIM.0b013 e3182 1b875 5
(2011).
5. Forrest, K. Y. Z. & Stuhldreher, W. L. Prevalence and correlates of vitamin D deciency in US adults. Nutr. Res. 31, 48–54. https ://
doi.org/10.1016/j.nutre s.2010.12.001 (2011).
6. Cashman, K. D. et al. Vitamin D deciency in Europe: Pandemic?. Am. J. Clin. Nutr. 103, 1033–1044. https ://doi.org/10.3945/
ajcn.115.12087 3 (2016).
7. Sharif, E. A. & Rizk, N. M. e prevalence of vitamin D deciency among female college students at Qatar University. Saudi Med.
J. 32, 964–965 (2011).
8. Al-Dabhani, K. et al. Prevalence of vitamin D deciency and association with metabolic syndrome in a Qatari population. Nutr.
Diabetes 7, e263. https ://doi.org/10.1038/nutd.2017.14 (2017).
9. Singh, P., Kumar, M. & Al Khodor, S. Vitamin D deciency in the gulf cooperation council: Exploring the triad of genetic pre-
disposition, the gut microbiome and the immune system. Front. Immunol. 10, 1042. https ://doi.org/10.3389/mmu .2019.01042
(2019).
10. Biobank, Q. (Qatar, 2019).
11. Manson, J. E. et al. Vitamin D supplements and prevention of cancer and cardiovascular disease. N. Engl. J. Med. 380, 33–44. https
://doi.org/10.1056/NEJMo a1809 944 (2019).
12. Giovannucci, E. et al. Prospective study of predictors of vitamin D status and cancer incidence and mortality in men. J. Natl. Cancer
Inst. 98, 451–459. https ://doi.org/10.1093/jnci/djj10 1 (2006).
13. Dobnig, H. et al. Independent association of low serum 25-hydroxyvitamin d and 1,25-dihydroxyvitamin d levels with all-cause
and cardiovascular mortality. Arch. Intern. Med. 168, 1340–1349. https ://doi.org/10.1001/archi nte.168.12.1340 (2008).
14. Afzal, S., Brondum-Jacobsen, P., Bojesen, S. E. & Nordestgaard, B. G. Vitamin D concentration, obesity, and risk of diabetes: A
mendelian randomisation study. Lancet Diabetes Endocrinol. 2, 298–306. https ://doi.org/10.1016/S2213 -8587(13)70200 -6 (2014).
15. Hypponen, E., Laara, E., Reunanen, A., Jarvelin, M. R. & Virtanen, S. M. Intake of vitamin D and risk of type 1 diabetes: A birth-
cohort study. Lancet 358, 1500–1503. https ://doi.org/10.1016/S0140 -6736(01)06580 -1 (2001).
16. Nielsen, O. H., Rejnmark, L. & Moss, A. C. Role of Vitamin D in the Natural History of Inammatory Bowel Disease. J. Crohns
Colitis 12, 742–752. https ://doi.org/10.1093/ecco-jcc/jjy02 5 (2018).
17. Garg, M. et al. e eect of vitamin D on intestinal inammation and faecal microbiota in patients with ulcerative colitis. J. Cro hn’s
Colitis 12, 963–972. https ://doi.org/10.1093/ecco-jcc/jjy05 2 (2018).
18. Kampmann, U. et al. Eects of 12 weeks high dose vitamin D3 treatment on insulin sensitivity, beta cell function, and metabolic
markers in patients with type 2 diabetes and vitamin D insuciency—a double-blind, randomized, placebo-controlled trial.
Metabolism 63, 1115–1124. https ://doi.org/10.1016/j.metab ol.2014.06.008 (2014).
Content courtesy of Springer Nature, terms of use apply. Rights reserved
Vol:.(1234567890)
Scientic Reports | (2020) 10:21641 |
www.nature.com/scientificreports/
19. Raery, T. et al. Eects of vitamin D supplementation on intestinal permeability, cathelicidin and disease markers in Crohn’s
disease: Results from a randomised double-blind placebo-controlled study. United Eur. Gastroenterol. J. 3, 294–302. https ://doi.
org/10.1177/20506 40615 57217 6 (2015).
20. Barengolts, E. Vitamin D and prebiotics may benet the intestinal microbacteria and improve glucose homeostasis in prediabetes
and type 2 diabetes. Endocr. Pract. 19, 497–510. https ://doi.org/10.4158/EP122 63.RA (2013).
21. Cantorna, M. T. et al. Vitamin D regulates the microbiota to control the numbers of RORgammat/FoxP3+ regulatory T cells in
the colon. Front. Immunol. 10, 1772. https ://doi.org/10.3389/mmu .2019.01772 (2019).
22. Luthold, R. V., Fernandes, G. R., Franco-de-Moraes, A. C., Folchetti, L. G. & Ferreira, S. R. Gut microbiota interactions with the
immunomodulatory role of vitamin D in normal individuals. Metabolism 69, 76–86. https ://doi.org/10.1016/j.metab ol.2017.01.007
(2017).
23. Kanhere, M. et al. Bolus weekly vitamin D3 supplementation impacts gut and airway microbiota in adults with cystic brosis:
A double-blind, randomized, placebo-controlled clinical trial. J. Clin. Endocrinol. Metab. 103, 564–574. https ://doi.org/10.1210/
jc.2017-01983 (2018).
24. Cantarel, B. L. et al. Gut microbiota in multiple sclerosis: Possible inuence of immunomodulators. J. Investig. Med. 63, 729–734.
https ://doi.org/10.1097/JIM.00000 00000 00019 2 (2015).
25. Ciubotaru, I., Green, S. J., Kukreja, S. & Barengolts, E. Signicant dierences in fecal microbiota are associated with various stages
of glucose tolerance in African American male veterans. Transl. Res. 166, 401–411. ht t ps ://do i .o r g/10.1016/j .trsl .2015.06.015 (2015).
26. Waterhouse, M. et al. Vitamin D and the gut microbiome: A systematic review of invivo studies. Eur. J. Nut r. 58, 2895–2910. https
://doi.org/10.1007/s0039 4-018-1842-7 (2019).
27. Naderpoor, N. et al. Eect of vitamin D supplementation on faecal microbiota: A randomised clinical trial. Nutrients https ://doi.
org/10.3390/nu111 22888 (2019).
28. Bashir, M. et al. Eects of high doses of vitamin D3 on mucosa-associated gut microbiome vary between regions of the human
gastrointestinal tract. Eur. J. Nutr. 55, 1479–1489. https ://doi.org/10.1007/s0039 4-015-0966-2 (2016).
29. Charoenngam, N., Shirvani, A., Kalajian, T. A., Song, A. & Holick, M. F. e eect of various doses of oral vitamin D3 supple-
mentation on gut microbiota in healthy adults: A randomized, double-blinded dose-response study. Anticancer Res. 40, 551–556.
https ://doi.org/10.21873 /antic anres .13984 (2020).
30. Aloia, J. F. et al. Vitamin D intake to attain a desired serum 25-hydroxyvitamin D concentration. Am. J. Clin. Nutr. 87, 1952–1958.
https ://doi.org/10.1093/ajcn/87.6.1952 (2008).
31. Gallagher, J. C., Sai, A., Templin, T. 2nd. & Smith, L. Dose response to vitamin D supplementation in postmenopausal women: A
randomized trial. Ann. Intern. Med. 156, 425–437. https ://doi.org/10.7326/0003-4819-156-6-20120 3200-00005 (2012).
32. Heaney, R. P., Davies, K. M., Chen, T. C., Holick, M. F. & Barger-Lux, M. J. Human serum 25-hydroxycholecalciferol response to
extended oral dosing with cholecalciferol. Am. J. Clin. Nutr. 77, 204–210. https ://doi.org/10.1093/ajcn/77.1.204 (2003).
33. Talwar, S. A., Aloia, J. F., Pollack, S. & Yeh, J. K. Dose response to vitamin D supplementation among postmenopausal African
American women. Am. J. Clin. Nutr. 86, 1657–1662. https ://doi.org/10.1093/ajcn/86.5.1657 (2007).
34. Carlberg, C. & Haq, A. e concept of the personal vitamin D response index. J. Steroid Biochem. Mol. Biol. 175, 12–17. https ://
doi.org/10.1016/j.jsbmb .2016.12.011 (2018).
35. Zittermann, A., Ernst, J. B., Gummert, J. F. & Borgermann, J. Vitamin D supplementation, body weight and human serum
25-hydroxyvitamin D response: A systematic review. Eur. J. N utr. 53, 367–374. https ://doi.org/10.1007/s0039 4-013-0634-3 (2014).
36. Holick, M. F. et al. Evaluation, treatment, and prevention of vitamin D deciency: An Endocrine Society clinical practice guideline.
J. Clin. Endocrinol. Metab. 96, 1911–1930. https ://doi.org/10.1210/jc.2011-0385 (2011).
37. 37Al-Daghri, N. M. et al. IGF and IGFBP as an index for discrimination between vitamin D supplementation responders and
nonresponders in overweight Saudi subjects. Medicine (Baltimore) 97, e0702, doi:https ://doi.org/10.1097/MD.00000 00000 01070
2 (2018).
38. Al-Daghri, N. M. et al. Ecacy of vitamin D supplementation according to vitamin D-binding protein polymorphisms. Nutrition
63–64, 148–154. https ://doi.org/10.1016/j.nut.2019.02.003 (2019).
39. Iruzubieta, P., Teran, A., Crespo, J. & Fabrega, E. Vitamin D deciency in chronic liver disease. World J. Hepatol. 6, 901–915. https
://doi.org/10.4254/wjh.v6.i12.901 (2014).
40. Franca Gois, P. H., Wolley, M., Ranganathan, D. & Seguro, A. C. Vitamin D deciency in chronic kidney disease: Recent evidence
and controversies. Int. J. Environ. Res. Public Health 15, 50. https ://doi.org/10.3390/ijerp h1508 1773 (2018).
41. Bentli, R. et al. Signicant independent predictors of vitamin D deciency in inpatients and outpatients of a nephrology unit. Int.
J. Endocrinol. 2013, 5. https ://doi.org/10.1155/2013/23786 9 (2013).
42. Bahreynian, M. et al. Association of Serum 25-hydroxyvitamin D levels and liver enzymes in a nationally representative sample
of Iranian adolescents: e childhood and adolescence surveillance and prevention of adult noncommunicable disease study. Int.
J. Prev. Med. 9, 24. https ://doi.org/10.4103/ijpvm .IJPVM _37_18 (2018).
43. Arumugam, M. et al. Enterotypes of the human gut microbiome. Nature 473, 174–180. https ://doi.org/10.1038/n atur e0994 4 (2011).
44. Eckburg, P. B. et al. Diversity of the human intestinal microbial ora. Science 308, 1635–1638. h t t ps ://do i .o r g/10.1126/scien ce .11105
91 (2005).
45. Kuznetsova, A., Brockho, P. B. & Christensen, R. H. lmerTest package: Tests in linear mixed eects models. J. Stat. Sow. 82, 1–26
(2017).
46. Langille, M. G. et al. Predictive functional proling of microbial communities using 16S rRNA marker gene sequences. Nat.
Biotechnol. 31, 814–821. https ://doi.org/10.1038/nbt.2676 (2013).
47. Rossi, M., Amaretti, A. & Raimondi, S. Folate production by probiotic bacteria. Nutrients 3, 118–134. https ://doi.org/10.3390/
nu301 0118 (2011).
48. D’Aimmo, M. R., Mattarelli, P., Biavati, B., Carlsson, N. G. & Andlid, T. e potential of bidobacteria as a source of natural folate.
J. Appl. Microbiol. 112, 975–984. https ://doi.org/10.1111/j.1365-2672.2012.05261 .x (2012).
49. Guasch-Ferre, M. et al. Metabolomics in prediabetes and diabetes: A systematic review and meta-analysis. Diabetes Care 39,
833–846. https ://doi.org/10.2337/dc15-2251 (2016).
50. Neis, E. P., Dejong, C. H. & Rensen, S. S. e role of microbial amino acid metabolism in host metabolism. Nutrients 7, 2930–2946.
https ://doi.org/10.3390/nu704 2930 (2015).
51. Ley, R. E., Turnbaugh, P. J., Klein, S. & Gordon, J. I. Microbial ecology: Human gut microbes associated with obesity. Nature 444,
1022–1023. https ://doi.org/10.1038/44410 22a (2006).
52. Sanz, Y. & Moya-Perez, A. Microbiota, inammation and obesity. Adv. Exp. Med. Biol. 817, 291–317. https ://do i.org/10.1007/978-
1-4939-0897-4_14 (2014).
53. Mariat, D. et al. e rmicutes/bacteroidetes ratio of the human microbiota changes with age. BMC Microbiol. 9, 123. https ://doi.
org/10.1186/1471-2180-9-123 (2009).
54. Yang, T. et al. Gut dysbiosis is linked to hypertension. Hypertension 65, 1331–1340. https ://doi.org/10.1161/HYPER TENSI ONAHA
.115.05315 (2015).
55. Everard, A. et al. Responses of gut microbiota and glucose and lipid metabolism to prebiotics in genetic obese and diet-induced
leptin-resistant mice. Diabetes 60, 2775–2786. https ://doi.org/10.2337/db11-0227 (2011).
56. Miller, R. S. & Hoskins, L. C. Mucin degradation in human colon ecosystems. Fecal population densities of mucin-degrading
bacteria estimated by a “most probable number” method. Gastroenterology 81, 759–765 (1981).
Content courtesy of Springer Nature, terms of use apply. Rights reserved
Vol.:(0123456789)
Scientic Reports | (2020) 10:21641 |
www.nature.com/scientificreports/
57. Derrien, M. et al. Mucin-bacterial interactions in the human oral cavity and digestive tract. Gut Microbes 1, 254–268. https ://doi.
org/10.4161/gmic.1.4.12778 (2010).
58. Derrien, M., Collado, M. C., Ben-Amor, K., Salminen, S. & de Vos, W. M. e Mucin degrader Akkermansia muciniphila is an
abundant resident of the human intestinal tract. Appl. Environ. Microbiol. 74, 1646–1648. htt ps ://doi.org/10.1128/AEM.01226 -07
(2008).
59. Everard, A. et al. Cross-talk between Akkermansia muciniphila and intestinal epithelium controls diet-induced obesity. Proc. Natl.
Acad. Sci. USA 110, 9066–9071. https ://doi.org/10.1073/pnas.12194 51110 (2013).
60. Shin, N. R. et al. An increase in the Akkermansia spp. population induced by metformin treatment improves glucose homeostasis
in diet-induced obese mice. Gut 63, 727–735. https ://doi.org/10.1136/gutjn l-2012-30383 9 (2014).
61. Hansen, C. H. et al. A maternal gluten-free diet reduces inammation and diabetes incidence in the ospring of NOD mice.
Diabetes 63, 2821–2832. https ://doi.org/10.2337/db13-1612 (2014).
62. Roopchand, D. E. et al. Dietary polyphenols promote growth of the gut bacterium akkermansia muciniphila and attenuate high-fat
diet-induced metabolic syndrome. Diabetes 64, 2847–2858. https ://doi.org/10.2337/db14-1916 (2015).
63. Hansen, C. H. et al. Early life treatment with vancomycin propagates Akkermansia muciniphila and reduces diabetes incidence
in the NOD mouse. Diabetologia 55, 2285–2294. https ://doi.org/10.1007/s0012 5-012-2564-7 (2012).
64. Ruiz, L., Delgado, S., Ruas-Madiedo, P., Sanchez, B. & Margolles, A. Bidobacteria and their molecular communication with the
immune system. Front. Microbiol. 8, 2345. https ://doi.org/10.3389/fmicb .2017.02345 (2017).
65. Pompei, A. et al. Administration of folate-producing bidobacteria enhances folate status in Wistar rats. J. Nutr. 137, 2742–2746.
https ://doi.org/10.1093/jn/137.12.2742 (2007).
66. Wu, G. D. et al. Linking long-term dietary patterns with gut microbial enterotypes. Science (New York, N.Y.) 334, 105–108. https
://doi.org/10.1126/scien ce.12083 44 (2011).
67. Rigsbee, L. et al. Quantitative proling of gut microbiota of children with diarrhea-predominant irritable bowel syndrome. Am.
J. Gastroenterol. https ://doi.org/10.1038/ajg.2012.287 (2012).
68. Scher, J. U. et al. Expansion of intestinal Prevotella copri correlates with enhanced susceptibility to arthritis. eLife 2, e01202. https
://doi.org/10.7554/eLife .01202 (2013).
69. Wu, S. et al. Vitamin D receptor negatively regulates bacterial-stimulated NF-kappaB activity in intestine. Am. J. Pathol. 177,
686–697. https ://doi.org/10.2353/ajpat h.2010.09099 8 (2010).
70. Sun, J. Vitamin D and mucosal immune function. Curr. Opin. Gastroenterol. 26, 591–595. htt ps ://do i .o r g/10.1097/m og.0b013 e3283
3d4b9 f (2010).
71. Wu, S. et al. Intestinal epithelial vitamin D receptor deletion leads to defective autophagy in colitis. Gut 64, 1082–1094. https ://
doi.org/10.1136/gutjn l-2014-30743 6 (2015).
72. Jin, D. et al. Lack of vitamin D receptor causes dysbiosis and changes the functions of the murine intestinal microbiome. Clin.
er. 37, 996-1009.e1007. https ://doi.org/10.1016/j.clint hera.2015.04.004 (2015).
73. Du, J. et al. 1,25-Dihydroxyvitamin D protects intestinal epithelial barrier by regulating the myosin light chain kinase signaling
pathway. Inamm. Bowel Dis. 21, 2495–2506. https ://doi.org/10.1097/mib.00000 00000 00052 6 (2015).
74. Zhang, Y. G. et al. Tight junction CLDN2 gene is a direct target of the vitamin D receptor. Sci. Rep. 5, 10642. https ://doi.org/10.1038/
srep1 0642 (2015).
75. Golan, M. A. et al. Transgenic expression of vitamin D receptor in gut epithelial cells ameliorates spontaneous colitis caused by
interleukin-10 deciency. Dig. Dis. Sci. 60, 1941–1947. https ://doi.org/10.1007/s1062 0-015-3634-8 (2015).
76. Appleyard, C. B. et al. Pretreatment with the probiotic VSL# 3 delays transition from inammation to dysplasia in a rat model of
colitis-associated cancer. Am. J. Physiol. Gastrointest. Liver Physiol. 301, 1004–1013 (2011).
77. Waterhouse, J. C., Perez, T. H. & Albert, P. J. Reversing bacteria-induced vitamin D receptor dysfunction is key to autoimmune
disease. Ann. N. Y. Acad. Sci. 1173, 757–765. https ://doi.org/10.1111/j.1749-6632.2009.04637 .x (2009).
78. Fangmann, D. et al. Targeted microbiome intervention by microencapsulated delayed-release niacin benecially aects insulin
sensitivity in humans. Diabetes Care 41, 398–405. https ://doi.org/10.2337/dc17-1967 (2018).
79. Iqbal, J. & Hussain, M. M. Intestinal lipid absorption. Am. J. Physiol. Endocrinol. Metab. 296, E1183-1194. https ://doi.org/10.1152/
ajpen do.90899 .2008 (2009).
80. ompson, G. R. Lipid related consequences of intestinal malabsorption. Gut 30 Spec No, 29–34. https ://doi.org/10.1136/gut.30.
spec_no.29 (1989).
81. Maurya, V. K. & Aggarwal, M. Factors inuencing the absorption of vitamin D in GIT: An overview. J. Food Sci. Technol. 54,
3753–3765. https ://doi.org/10.1007/s1319 7-017-2840-0 (2017).
82. Yang, J. Y. et al. Gut commensal Bacteroides acidifaciens prevents obesity and improves insulin sensitivity in mice. Mucosal Immu-
nol. 10, 104–116. https ://doi.org/10.1038/mi.2016.42 (2017).
83. Bolyen, E. et al. Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2. Nat. Biotechnol. 37,
852–857. https ://doi.org/10.1038/s4158 7-019-0209-9 (2019).
84. Caporaso, J. G. et al. QIIME allows analysis of high-throughput community sequencing data. Nat. Methods 7, 335–336. https ://
doi.org/10.1038/nmeth .f.303 (2010).
85. Callahan, B. J. et al. DADA2: High-resolution sample inference from Illumina amplicon data. Nat. Methods 13, 581–583. https ://
doi.org/10.1038/nmeth .3869 (2016).
86. DeSantis, T. Z. et al. Greengenes, a chimera-checked 16S rRNA gene database and workbench compatible with ARB. Appl. Environ.
Microbiol. 72, 5069–5072. https ://doi.org/10.1128/AEM.03006 -05 (2006).
87. R Core Team, R. (R foundation for statistical computing Vienna, Austria, 2013).
88. McMurdie, P. J. & Holmes, S. phyloseq: An R package for reproducible interactive analysis and graphics of microbiome census
data. PLoS ONE 8, e61217. https ://doi.org/10.1371/journ al.pone.00612 17 (2013).
89. Weiss, S. et al. Normalization and microbial dierential abundance strategies depend upon data characteristics. Microbiome 5, 27.
https ://doi.org/10.1186/s4016 8-017-0237-y (2017).
90. Chao, A. Estimating the population size for capture-recapture data with unequal catchability. Biometrics 43, 783–791 (1987).
91. Shannon, C. E. A mathematical theory of communication, Part II. Bell Syst. Tech. J. 27, 623–656 (1948).
92. Simpson, E. H. Measurement of diversity. Nature 163, 688–688. https ://doi.org/10.1038/16368 8a0 (1949).
93. Jari Oksanen, F. G. B., Michael Friendly, Roeland Kindt, Pierre Legendre, D. M., Peter R. Minchin, R. B. O’Hara,, Gavin L. Simpson,
P. S., M. Henry H. Stevens, Eduard Szoecs, & Wagner, H. (2019).
94. Bates, D., Mächler, M., Bolker, B. & Walker, S. Fitting Linear Mixed-Eects Models Using lme4. 67, 48. https ://doi.org/10.18637 /
jss.v067.i01 (2015).
95. Parks, D. H., Tyson, G. W., Hugenholtz, P. & Beiko, R. G. STAMP: Statistical analysis of taxonomic and functional proles. Bioin-
formatics 30, 3123–3124. https ://doi.org/10.1093/bioin forma tics/btu49 4 (2014).
96. Love, M. I., Huber, W. & Anders, S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome
Biol. 15, 550. https ://doi.org/10.1186/s1305 9-014-0550-8 (2014).
97. Kashani, A. et al. Impaired glucose metabolism and altered gut microbiome despite calorie restriction of ob/ob mice. Anim.
Microbiome 1, 11. https ://doi.org/10.1186/s4252 3-019-0007-1 (2019).
Content courtesy of Springer Nature, terms of use apply. Rights reserved
Vol:.(1234567890)
Scientic Reports | (2020) 10:21641 |
www.nature.com/scientificreports/
Acknowledgements
We would like to acknowledge Dr. Lucy Robinson from Insight Editing for the technical editing and proof read-
ing of the manuscript. Dr. Nasser Rizk for his help in planning the project
Author contributions
S.K. designed the study. S.K. and E.S. planned the study. E.S. received funding for the study. M.A. and E.S.
recruited the study subjects and performed the biochemical analysis. PS processed the samples and AR analyzed
the data. All authors discussed the results. P.S. wrote the rst dra of the manuscript. All authors reviewed and
approved the submitted version of the manuscript.
Funding
Qatar University Internal grant. Grant ID: QUCP-CHS- 17\18–1.
Competing interests
e authors declare no competing interests.
Additional information
Supplementary information is available for this paper at https ://doi.org/10.1038/s4159 8-020-77806 -4.
Correspondence and requests for materials should be addressed to E.S.orS.K.
Reprints and permissions information is available at www.nature.com/reprints.
Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and
institutional aliations.
Open Access is article is licensed under a Creative Commons Attribution 4.0 International
License, which permits use, sharing, adaptation, distribution and reproduction in any medium or
format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the
Creative Commons licence, and indicate if changes were made. e images or other third party material in this
article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the
material. If material is not included in the article’s Creative Commons licence and your intended use is not
permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from
the copyright holder. To view a copy of this licence, visit http://creat iveco mmons .org/licen ses/by/4.0/.
© e Author(s) 2020
Content courtesy of Springer Nature, terms of use apply. Rights reserved
1.
2.
3.
4.
5.
6.
Terms and Conditions
Springer Nature journal content, brought to you courtesy of Springer Nature Customer Service Center GmbH (“Springer Nature”).
Springer Nature supports a reasonable amount of sharing of research papers by authors, subscribers and authorised users (“Users”), for small-
scale personal, non-commercial use provided that all copyright, trade and service marks and other proprietary notices are maintained. By
accessing, sharing, receiving or otherwise using the Springer Nature journal content you agree to these terms of use (“Terms”). For these
purposes, Springer Nature considers academic use (by researchers and students) to be non-commercial.
These Terms are supplementary and will apply in addition to any applicable website terms and conditions, a relevant site licence or a personal
subscription. These Terms will prevail over any conflict or ambiguity with regards to the relevant terms, a site licence or a personal subscription
(to the extent of the conflict or ambiguity only). For Creative Commons-licensed articles, the terms of the Creative Commons license used will
apply.
We collect and use personal data to provide access to the Springer Nature journal content. We may also use these personal data internally within
ResearchGate and Springer Nature and as agreed share it, in an anonymised way, for purposes of tracking, analysis and reporting. We will not
otherwise disclose your personal data outside the ResearchGate or the Springer Nature group of companies unless we have your permission as
detailed in the Privacy Policy.
While Users may use the Springer Nature journal content for small scale, personal non-commercial use, it is important to note that Users may
not:
use such content for the purpose of providing other users with access on a regular or large scale basis or as a means to circumvent access
control;
use such content where to do so would be considered a criminal or statutory offence in any jurisdiction, or gives rise to civil liability, or is
otherwise unlawful;
falsely or misleadingly imply or suggest endorsement, approval , sponsorship, or association unless explicitly agreed to by Springer Nature in
writing;
use bots or other automated methods to access the content or redirect messages
override any security feature or exclusionary protocol; or
share the content in order to create substitute for Springer Nature products or services or a systematic database of Springer Nature journal
content.
In line with the restriction against commercial use, Springer Nature does not permit the creation of a product or service that creates revenue,
royalties, rent or income from our content or its inclusion as part of a paid for service or for other commercial gain. Springer Nature journal
content cannot be used for inter-library loans and librarians may not upload Springer Nature journal content on a large scale into their, or any
other, institutional repository.
These terms of use are reviewed regularly and may be amended at any time. Springer Nature is not obligated to publish any information or
content on this website and may remove it or features or functionality at our sole discretion, at any time with or without notice. Springer Nature
may revoke this licence to you at any time and remove access to any copies of the Springer Nature journal content which have been saved.
To the fullest extent permitted by law, Springer Nature makes no warranties, representations or guarantees to Users, either express or implied
with respect to the Springer nature journal content and all parties disclaim and waive any implied warranties or warranties imposed by law,
including merchantability or fitness for any particular purpose.
Please note that these rights do not automatically extend to content, data or other material published by Springer Nature that may be licensed
from third parties.
If you would like to use or distribute our Springer Nature journal content to a wider audience or on a regular basis or in any other manner not
expressly permitted by these Terms, please contact Springer Nature at
onlineservice@springernature.com
