lactobacillus gasseri in the upper small intestine impacts
TRANSCRIPT
Article
Lactobacillus gasseri in the
Upper Small IntestineImpacts an ACSL3-Dependent Fatty Acid-SensingPathway RegulatingWhole-Body Glucose HomeostasisGraphical Abstract
Highlights
d Upper small intestinal fatty acid-ACSL3 sensing impacts
glucose homeostasis
d HFD decreases Lactobacillus gasseri (LG) and disrupts
ACSL3-fatty acid sensing
d Regular chow microbiota transplant restores LG and ACSL3-
lipid sensing
d Lactobacillus gasseri administration restores ACSL3-lipid
sensing in HFD rodents
Bauer et al., 2018, Cell Metabolism 27, 572–587March 6, 2018 ª 2018 Elsevier Inc.https://doi.org/10.1016/j.cmet.2018.01.013
Authors
Paige V. Bauer, Frank A. Duca,
T.M. Zaved Waise, ..., Mozhgan Rasti,
Catherine A. O’Brien, Tony K.T. Lam
In Brief
Bauer et al. report that a glucoregulatory
pre-absorptive ACSL3-dependent fatty
acid-sensing pathway in the upper small
intestine is compromised by a high-fat
diet. Fatty acid sensing and glucose
homeostasis are restored by probiotic
Lactobacillus gasseri administration or by
transplantation of microbiota from chow-
fed animals.
Cell Metabolism
Article
Lactobacillus gasseri in the Upper Small IntestineImpacts an ACSL3-Dependent Fatty Acid-SensingPathwayRegulatingWhole-BodyGlucoseHomeostasisPaige V. Bauer,1,2 Frank A. Duca,1 T.M. Zaved Waise,1 Helen J. Dranse,1 Brittany A. Rasmussen,1,2 Akshita Puri,4
Mozhgan Rasti,1 Catherine A. O’Brien,2,4,5 and Tony K.T. Lam1,2,3,6,7,*1Toronto General Hospital Research Institute, UHN, MaRS Centre, Toronto Medical Discovery Tower, Room 10-705, 101 College Street,
Toronto, ON M5G 1L7, Canada2Department of Physiology, University of Toronto, Toronto, ON M5S 1A8, Canada3Department of Medicine, University of Toronto, Toronto, ON M5S 1A8, Canada4Princess Margaret Cancer Centre, UHN, Toronto, ON M5G 2M9, Canada5Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, ON M5S 1A8, Canada6Banting and Best Diabetes Centre, University of Toronto, Toronto, ON M5G 2C4, Canada7Lead Contact
*Correspondence: [email protected]
https://doi.org/10.1016/j.cmet.2018.01.013
SUMMARY
Long-chain acyl-CoA synthetase (ACSL)-dependentupper small intestinal lipid metabolism activatespre-absorptive pathways to regulate metabolic ho-meostasis, but whether changes in the upper smallintestinal microbiota alter specific fatty acid-depen-dent pathways to impact glucose homeostasis re-mains unknown. We here first find that upper smallintestinal infusion of Intralipid, oleic acid, or linoleicacid pre-absorptively increases glucose toleranceand lowers glucose production in rodents. High-fatfeeding impairs pre-absorptive fatty acid sensingand reduces upper small intestinal Lactobacillusgasseri levels and ACSL3 expression. Transplanta-tion of healthy upper small intestinal microbiota tohigh-fat-fed rodents restores L. gasseri levels andfatty acid sensing via increased ACSL3 expression,while L. gasseri probiotic administration to non-transplanted high-fat-fed rodents is sufficient torestore upper small intestinal ACSL3 expressionand fatty acid sensing. In summary, we unveil a glu-coregulatory role of upper small intestinal L. gasserithat impacts an ACSL3-dependent glucoregulatoryfatty acid-sensing pathway.
INTRODUCTION
Glucose intolerance is a risk factor for type 2 diabetes (Roglic
and World Health Organization, 2016). An elevation of glucose
production (GP) by the liver contributes to glucose intolerance
and is the result of impaired insulin secretion and action, as
well as defects in glucose effectiveness and nutrient-sensing
pathways in the gut and brain (Defronzo, 2009; Lam, 2010; Ros-
setti et al., 1990). Metformin and bariatric surgery are effective
therapies that improve glucose tolerance by lowering GP in dia-
572 Cell Metabolism 27, 572–587, March 6, 2018 ª 2018 Elsevier Inc
betes (Batterham andCummings, 2016; Hundal et al., 2000), and
the mechanisms are linked to a small intestinal nutrient sensing-
dependent neuronal network (Breen et al., 2012; Duca et al.,
2015b; Jiao et al., 2013). Metformin and bariatric surgery also
changes gut microbiota (Forslund et al., 2015; Tremaroli et al.,
2015;Wu et al., 2017), suggesting themicrobiota interact with in-
testinal nutrient sensing to impact glucose homeostasis.
The gut microbiota rapidly changes in response to a high-fat
diet (HFD) (David et al., 2014; Turnbaugh et al., 2009), and themi-
crobiota regulates body weight and adiposity (Backhed et al.,
2004; Ridaura et al., 2013; Turnbaugh et al., 2006). Despite prog-
ress in identifying functional and compositional alterations in the
fecal metagenome of type 2 diabetic individuals (Karlsson et al.,
2013; Qin et al., 2012), most studies have overlooked the role of
the microbiota residing in the upper small intestine, an important
site for nutrient sensing and metabolic regulation (Duca et al.,
2015a). For example, the transfer of feces from healthy individ-
uals to individuals with metabolic syndrome via a duodenal cath-
eter alters the fecal microbiota of recipients in association with
improvements in insulin sensitivity (Vrieze et al., 2012). This mi-
crobiota transfer could alter the microbial community in the up-
per small intestine, contributing to this insulin-sensitizing effect.
Similarly, pre- and probiotics improve glucose regulation and
robustly alter distal intestinal and fecal microbiota of rodents
and humans (Balakumar et al., 2016; Cani et al., 2006a; Ejtahed
et al., 2012; Everard andCani, 2013); however, these substances
must first pass the upper small intestine where they could elicit
their glucoregulatory effects. This is in line with the fact that
most probiotics are derived from Lactobacillus (Asemi et al.,
2013; Balakumar et al., 2016; Ejtahed et al., 2012; Yadav et al.,
2007), which is a prominent inhabitor of the small intestine (Gu
et al., 2013; Wirth et al., 2014).
The upper small intestine contacts ingested nutrients that
initiate negative feedback pathways to regulate glucose homeo-
stasis (Duca et al., 2015a). For example, lipid sensing (achieved
via Intralipid infusion) in the upper small intestine activates a gut-
brain axis to lower GP and plasma glucose levels (Wang et al.,
2008). This effect is dependent upon formation of long-chain
fatty acyl-coenzyme A (CoA) via long-chain acyl-CoA synthetase
.
Figure 1. Upper Small Intestinal Infusion of Intralipid, Oleic Acid, or Linoleic Acid, Increases Glucose Tolerance in RC but Not HFD Rodents
(A) Experimental procedure and intravenous glucose tolerance test (i.v.GTT) protocol.
(B–G) Percent change in plasma glucose levels (inset: integrated area under the curve [AUC]) (B, D, and F) and absolute plasma insulin levels (C, E, and G) during
the i.v.GTT in regular chow rats that received an upper small intestinal infusion of saline (n = 6), Intralipid (n = 6), PBS with bile salts (n = 6), oleic acid (n = 8), or
linoleic acid (n = 6).
(H–J) Percent change in plasma glucose levels (inset: integrated AUC) during the i.v.GTT in 3-day high-fat diet rats that received an upper small intestinal infusion
of saline (n = 7), Intralipid (n = 6) (H), PBS + bile salts (n = 6), oleic acid (n = 6) (I), or linoleic acid (n = 6) (J).
*p < 0.05, **p < 0.01, ***p < 0.001 determined by t test. Data are shown as the mean ± SEM. See also Table S1 and Figure S1. i.v.GTT, intravenous glucose
tolerance test; AUC, area under the curve; HFD, high-fat diet.
(ACSL), as general inhibition of ACSL isoforms in the upper small
intestine negates lipid sensing (Wang et al., 2008). This glucore-
gulatory lipid-sensing pathway is abolished in HFD rodents
(Cheung et al., 2009), but whether HFD feeding affects upper
small intestinal ACSL expression via changes in microbiota,
and whether this postulated change in ACSL expression affects
lipid sensing, is unknown. Interestingly, inoculation of germ-free
mice with the microbiota of healthy conventionally raised mice
alters the expression of hundreds of genes involved in glucose
and lipid metabolism in the upper and distal gut (Derrien et al.,
2011; El Aidy et al., 2013), including ACSL expression (El Aidy
et al., 2013), suggesting that the microbiota could alter intestinal
ACSL expression. Based on these findings, we tested the hy-
pothesis that upper small intestinal microbiota alter upper small
intestinal ACSL-dependent glucoregulatory fatty acid-sensing
pathways in rodents.
RESULTS
Upper Small Intestinal Fatty Acid-Sensing MechanismsIncrease Glucose Tolerance and Lower GP in Healthybut Not High-Fat-Fed RodentsTo begin addressing the potential interaction between the upper
small intestinal microbiota and glucoregulatory lipid-sensing
pathways, we first investigated whether gut lipid sensing regu-
lates whole-body glucose tolerance under physiological condi-
tions. Intralipid (lipid emulsion) was infused for a total of 50 min
into the upper small intestine of conscious, unrestrained, regular
chow (RC)-fed rats to activate pre-absorptive lipid-sensing path-
ways as described previously (Wang et al., 2008), and glucose
tolerance was assessed with an intravenous glucose toler-
ance test (i.v.GTT) (Figure 1A). Intralipid versus saline infusion
increased glucose tolerance (Figures 1B and S1A) independently
of a rise in plasma insulin levels (Figure 1C). To examine the effect
of individual fatty acids within Intralipid, oleic acid or linoleic acid
(prevalent fatty acids found in human circulation) was dissolved
in PBS with bile salts (containing 0.1% [wt/vol] lecithin and 1%
[wt/vol] sodium taurocholate) and infused for a total of 50 min
into the upper small intestine during the i.v.GTT. Both oleic
acid and linoleic acid improved glucose tolerance (Figures 1D,
1F, S1B, and S1C) independently of a rise in plasma insulin levels
(Figures 1E and 1G) when compared with an infusion of PBSwith
bile salts alone. Next, surgically recovered rats were given a
saturated fat-enriched HFD (Table S1) for 3 days, which has pre-
viously been shown to induce hyperphagia and hepatic insulin
resistance in rodents (Cote et al., 2015), before being subjected
to the i.v.GTTwith a gut infusion of Intralipid, oleic acid, or linoleic
acid. Rats exhibited hyperphagia in response to the HFD diet
(Figure S1D) but had comparable body weight (Figure S1E),
which is consistent with reports documenting that 3-day
Cell Metabolism 27, 572–587, March 6, 2018 573
Figure 2. Upper Small Intestinal Oleic Acid or Linoleic Acid Infusion Lowers GP through a Gut Peptide-Dependent Neuronal Network in RC
but Not HFD Rodents
(A) Experimental procedure for pancreatic (basal insulin)-euglycemic clamp protocol.
(B–D) The glucose infusion rate (B), glucose production (C), and glucose uptake (D) during the pancreatic clamps of healthy rats that received an upper small
intestinal infusion of saline (n = 12), PBS with bile salts (n = 7), oleic acid (n = 11), or linoleic acid (n = 7). **p < 0.01 versus saline and PBS with bile salts as
determined by ANOVA with Tukey’s post hoc test.
(E) Glucose production during clamps of healthy rats that received an upper small intestinal infusion of MK-329 (n = 7), Exendin-9 (n = 5), MK-329 + oleic acid
(n = 5), Exendin-9 + oleic acid (n = 6), MK-329 + linoleic acid (n = 5), or Exendin-9 + linoleic acid (n = 5). **p < 0.01 versus all other groups as determined by ANOVA
with Tukey’s post hoc test.
(F) Glucose production during clamps of healthy rats that received an upper small intestinal infusion of tetracaine (n = 5), tetracaine + oleic acid (n = 5), and
tetracaine + linoleic acid (n = 5).
(G) Glucose production during clamps in 3-day high-fat diet-fed rats that received an upper small intestinal infusion of saline (n = 5), oleic acid (n = 5), and linoleic
acid (n = 5). Values are shown asmean + SEM. See also Tables S1, S2, and Figure S2. SRIF, somatostatin; basal, the average GP over the period from 60 to 90min
during the pancreatic (basal insulin)-euglycemic clamp; clamp, the average GP from 180 to 200 min; Ex-9, exendin-9.
HFD-induced hyperphagia induces insulin and leptin resistance
but does not increase body weight in rodents (Morgan et al.,
2004; Scherer et al., 2012; Thaler et al., 2012). We found that up-
per small intestinal infusion of Intralipid, oleic acid, and linoleic
acid failed to improve glucose tolerance (Figures 1H, 1I, 1J,
S1F, S1G, and S1H) in HFD rats at comparable plasma insulin
levels (Figures S1I, S1J, and S1K). Thus, upper small intestinal
lipid (specifically oleic acid and linoleic acid) sensing, improves
glucose tolerance in healthy but not HFD rodents.
To determine whether upper small intestinal fatty acid-sensing
regulates glucose tolerance via gut-mediated changes in GP or
glucose uptake independent of changes in plasma insulin levels
(Table S2), oleic acid or linoleic acid were infused for 50 min
into the upper small intestine and changes in glucose kinetics
were evaluated via tracer dilution methodology under pancreatic
basal insulin-euglycemic clamp conditions (Figure 2A; Table S2).
During the oleic acid and linoleic acid gut infusion, the exoge-
574 Cell Metabolism 27, 572–587, March 6, 2018
nous glucose infusion rate increased by �5-fold relative to the
vehicle infusion to prevent a drop in plasma glucose levels and
to maintain euglycemia (Figure 2B; Table S2). This glucose-
lowering effect was due to a reduction in GP (Figure 2C) rather
than an increase in glucose uptake (Figure 2D). Of note, there
was no change in plasma or portal free fatty acid levels at the
end of the 50 min gut infusion relative to the pre-infused basal
condition, as well as between treatment groups (Figure S2A),
ensuring the effects seen throughout the clamp and i.v.GTT
(Figures 1 and S1) are due to pre-absorptive fatty acid sensing
in healthy rats. In addition, the ability of oleic acid and linoleic
acid to lower GP is conserved in healthy mice during the basal
insulin pancreatic clamp (Figures S2B–S2E). Together with the
fact that upper small intestinal Intralipid infusion lowers GP
(Wang et al., 2008), our data collectively indicate that upper small
intestinal fatty acid sensing increases glucose tolerance at least
in part by lowering GP in rats and mice in vivo.
Increased consumption of oleic acid and linoleic acid has
beneficial glucoregulatory effects in rodents and humans (Ris-
erus et al., 2009); however, the mechanisms involved have
beendebated. Although Intralipid infusion into the upper small in-
testine activates a CCK-1 receptor-dependent pathway to lower
GP (Cheung et al., 2009), oleic acid stimulates the release of both
CCK (Chang et al., 2000) and GLP-1 (Iakoubov et al., 2007)
in vitro. While CCK appears to mediate the satiety response to
a duodenal infusion of oleic acid (Woltman and Reidelberger,
1995), the glucoregulatory effects of diets high in oleic acid
havebeenattributed toGLP-1action (Rocca et al., 2001). Linoleic
acid also stimulates the release of CCK (Shah et al., 2012) and
GLP-1 (Richards et al., 2016) in vitro; however, intestinal linoleic
acid infusion lowers food intake through a GLP-1-dependent
mechanism (Dailey et al., 2011). Thus, to evaluate whether a
gut CCK- and/or GLP-1-dependent pathway is necessary for up-
per small intestinal fatty acid sensing, each fatty acid was co-
infused with the CCK-1 receptor inhibitor MK-329 or the GLP-1
receptor (GLP-1R) inhibitor Exendin-9. Co-infusion of oleic acid
with either MK-329 or Exendin-9 abolished the ability of an oleic
acid 50 min infusion to increase the glucose infusion rate (Fig-
ure S2F) and decrease GP (Figure 2E) with no change in glucose
uptake (Figure S2G) during the pancreatic clamp, suggesting
(although warrants future investigation) that oleic acid-induced
CCK-1 receptor and GLP-1R effect is additive in the current
experimental context. In contrast, co-infusion of MK-329 with li-
noleic acid did not influence the ability of linoleic acid to decrease
GP (Figures 2E, S2F, and S2G) compared with MK-329 alone
(Figures 2E, S2F, and S2G). However, co-infusion of Exendin-9
with linoleic acid negated the ability of linoleic acid to regulate
glucose metabolism compared with Exendin-9 alone (Figures
2E, S2F, and S2G). Therefore, oleic acid activates CCK-1- and
GLP-1R-dependent pathways, while linoleic acid stimulates a
CCK-1-independent and GLP-1R-dependent pathway in the up-
per small intestine to lower GP in healthy rats. The underlying
mechanisms responsible for the oleic acid- versus linoleic acid-
induced differential effect on the gut peptide-dependent glucor-
egulatory pathways warrant future investigation.
To determine whether a downstream neuronal pathway is
necessary for oleic acid and linoleic acid sensing, each fatty
acid was co-infused into the upper small intestine with the local
anesthetic, tetracaine. Infusion of tetracaine alone had no meta-
bolic consequences but negated the ability of both fatty acids to
increase the glucose infusion rate (Figure S2H) and lower GP
(Figure 2F) with no effect on glucose uptake (Figure S2I), indi-
cating that a gut-brain neuronal network is required for the
suppressive effects of these fatty acids on GP. Taken together,
oleic and linoleic acids trigger a common GLP-1R-dependent
neuronal network to lower GP in healthy rats.
To address the pathological relevance of these GP-lowering
pathways, oleic acid or linoleic acid were infused into the upper
small intestine of HFD rats. These HFD rats were hyperphagic
relative to their RC counterparts (Figure S2J), but were not obese
(Figure S2K). During the pancreatic clamps, oleic acid and
linoleic acid failed to increase the glucose infusion rate (Fig-
ure S2L) and lower GP (Figure 2G) compared with RC-fed rats,
while glucose uptake remained unaltered (Figure S2M). Taken
together with the i.v.GTT data, we have validated, via three
different fatty acid treatments using two complementary tests,
that an HFD disrupts specific upper small intestinal fatty acid-
sensing pathways, leading to a dysregulation of GP and glucose
tolerance.
Upper Small Intestinal Microbiota Transplantation fromRC-Fed Donors Normalizes the Upper Small IntestinalMicrobiota in HFD Recipient RatsA potential link between HFD and impaired upper small intestinal
fatty acid sensing could be diet-induced changes in the gut mi-
crobiota. Indeed, the gut microbiota rapidly changes in response
to an HFD (David et al., 2014; Turnbaugh et al., 2009), and
increasing evidence suggests the gut microbiota plays an impor-
tant role in glucose homeostasis (Kovatcheva-Datchary et al.,
2015; Plovier et al., 2017; Shin et al., 2014; Vrieze et al., 2012;
Wu et al., 2017), as a recent study indicates metformin alters mi-
crobiota composition in the upper small intestine to impact a
glucose-sensing mechanism that regulates GP as well (Bauer
et al., 2018). More importantly, conventionalization of germ-
free mice alters the expression of proteins involved in upper
small intestinal lipid sensing, such as CD36, FABP4, and ACSL
(Derrien et al., 2011; El Aidy et al., 2013). Thus, we investigated
whether an upper small intestinal microbiota transplant from
RC-fed donors could normalize the upper small intestinal micro-
biota in HFD-recipient rats, and whether the change in upper
small intestinal microbiota of transplanted HFD rats could rescue
fatty acid-sensing mechanisms.
We first characterized themicrobiota composition in the upper
small intestine of RC and HFD rats, as well as HFD rats receiving
an upper small intestinal RCmicrobiota transplant. To ensure the
microbiota transplants were targeted to the upper small intes-
tine, upper small intestinal luminal contents of the donor rats
were transplanted into recipient rats by slowly administering
the transplanted material over the course of 30 s via the upper
small intestinal cannula. RC, HFD, and HFD rats receiving an
upper small intestinal RC microbiota transplant received a gut
saline infusion and were sacrificed following the pancreatic
clamp studies. The luminal contents were collected from the up-
per small intestine (between 6 and 15 cm distal to the pyloric
sphincter), and the variable region 3 (V3) of the bacterial 16S
rRNA gene was amplified by PCR and sequenced using an Illu-
mina MiSeq platform (Table S3). Of note, the luminal contents
used for bacterial transplantation and sequencing were from
the same region of the small intestine.
Principal coordinate analysis of weighted UniFrac distance
between the upper small intestinal samples from each group
showed a clear separation between RC and HFD communities
(Figure 3A), while samples from HFD rats that received an upper
small intestinal RCmicrobiota transplant clustered with RC sam-
ples and were well separated from HFD samples (Figure 3A).
Analysis at the phylum level indicated that the upper small intes-
tinal microbiota in all three groups was dominated by two phyla:
Firmicutes and Proteobacteria (Figure 3B). The high abundance
of Firmicutes in these groups (especially in the RC or the HFD
rats transplanted with RC microbiota) is consistent with studies
characterizing the upper small intestinal microbiota in RC mice
(Gu et al., 2013) and RC Wistar rats (Wirth et al., 2014), as well
as in the cecum and feces of RC Sprague-Dawley rats (Di Luccia
et al., 2015; Liu et al., 2015). HFD increased the relative abun-
dance of Proteobacteria and reduced relative abundance of
Cell Metabolism 27, 572–587, March 6, 2018 575
Figure 3. HFD-Induced Changes in the Upper Small Intestinal Microbiota Can Be Reversed with a Microbiota Transplant from RC Rats
(A) Principal coordinate analysis of weighted UniFrac displays separation between samples from RC rats, HFD rats, and HFD rats that received an upper small
intestinal RC microbiota transplant (HFDwRCM). The percentage of variation explained by the plotted principal coordinates is indicated in the axis labels. Each
dot represents an upper small intestinal community from one rat.
(B) Relative abundance at the phylum level in the upper small intestinal community of RC, HFD, and HFDwRCM rats. Each column corresponds to one sample.
(C) Relative abundance of families that are significantly altered by HFD feeding and restored with the upper small intestinal RC microbiota transplant (expressed
as a percent of the total upper small intestinal community). **p < 0.01, ***p < 0.001HFD versus all other groups, as assessed by ANOVAwith Tukey’s post hoc test.
Values are shown as the mean + SEM.
(D) Relative abundance at the genus level in the upper small intestinal community of RC, HFD, or HFDwRCM rats. Each column corresponds to one sample.
(E) Heatmap of the relative abundance of species from the Lactobacillus genus. Each row corresponds to one sample. **p < 0.01 HFD versus all other groups, as
assessed by ANOVAwith Tukey’s post hoc test. See also Table S3 and Figure S3. RC, regular chow (n = 6); HFD, high-fat diet (n = 6); HFDwRCM, high-fat diet with
RC microbiota transplant (n = 5).
Firmicutes compared with RC rats (Figure 3B and Table S3, as
identified by LefSE and assessed by ANOVA). At the family level,
HFD versus RC reduced Lactobacillaceae and modestly yet
significantly increased Clostridiaceae (both Lactobacillaceace
and Clostridiaceae are from the Firmicutes Phylum) (Figure 3C;
Table S3). At the genus level, and consistent with previous liter-
ature (Almiron et al., 2013), the upper small intestinal microbiota
of RC rats was dominated by Lactobacillus (Figure 3D; Table S3).
However, the abundance of Lactobacillus was reduced in
response to HFD (Figure 3D; Table S3). Importantly, analysis
(as identified by LefSE and assessed by ANOVA) of the upper
small intestinal luminal contents of HFD rats transplanted with
576 Cell Metabolism 27, 572–587, March 6, 2018
RC microbiota revealed that HFD-induced changes in the upper
small intestinal microbiota at the phylum (Firmicutes and Proteo-
bacteria) (Figure 3B; Table S3), family (Lactobacillaceae and
Clostridiaceae) (Figure 3C; Table S3), and genus (Lactobacillus)
(Figure 3D; Table S3) levels were all reversed to RC conditions
with transplantation of upper small intestinal RC microbiota.
We next performed a detailed characterization of the species
within the Lactobacillus genus and found that HFD versus
RC reduced the abundance of Lactobacillus (L.) gasseri and
increased L. animalis, while the effect of HFD on L. gasseri and
L. animalis were abolished in HFD rats transplanted with upper
small intestinal RC microbiota (Figure 3E; Table S3). Of note,
Figure 4. Transplantation of Upper Small Intestinal RCMicrobiota Restores Fatty Acid-Sensing Pathways that IncreaseGlucose Tolerance inHFD Rodents
(A) Experimental procedure of the microbiota transplant protocol.
(B andC) Percent change in plasma glucose levels (inset: integrated AUC) (B) and absolute plasma insulin levels (C) during the i.v.GTT in HFD rats that received an
RC upper small intestinal microbiota transplant and an upper small intestinal saline (n = 6) or Intralipid (n = 6) infusion and HFD rats that received an HFD upper
small intestinal microbiota transplant and an upper small intestinal saline (n = 6) or Intralipid (n = 6) infusion.
(D) Percent change in plasma glucose levels (inset: integrated AUC) during the i.v.GTT in HFD rats that received heat-shock (n = 6) or filtered (n = 5) RC upper small
intestinal microbiota and an upper small intestinal Intralipid infusion.
(E) Percent change in plasma glucose levels (inset: integrated AUC) during the i.v.GTT in HFD rats that received a colonic RCmicrobiota transplant and an upper
small intestinal saline (n = 5) or Intralipid (n = 5) infusion.
*p < 0.05, **p < 0.01 HFD + RCM + Intralipid versus all other groups, as assessed by ANOVA with Tukey’s post hoc test. Values are shown as mean ± SEM. See
also Figure S4. IVGTT, intravenous glucose tolerance test; RC, regular chow; HFD, high-fat diet.
all changes in the microbiota among the three groups occurred
in the context of comparable bacterial diversity (Figure S3).
Thus, HFD-induced changes in upper small intestinal microbiota
composition can be reversed in HFD rats with a direct upper
small intestinal RC microbiota transplant.
Upper Small Intestinal Microbiota Transplantation fromRC-Fed Donors Restores Upper Small Intestinal FattyAcid-Sensing Mechanisms in HFD-Recipient RatsGiven that an HFD disrupts selective upper small intestinal fatty
acid-sensing pathways and glucose homeostasis (Figures 1
and 2) in parallel to changes in upper small intestinal microbiota
composition (Figure 3), and that an upper small intestinal RC mi-
crobiota transplant is sufficient to normalize upper small intesti-
nal microbiota in HFD rats (Figure 3), we next assessed the glu-
coregulatory relationship between the gut microbiota and fatty
acid-sensing mechanisms in the transplanted rats (Figure 4A).
We found that upper small intestinal infusion of Intralipid versus
saline improved glucose tolerance in HFD rats that received an
upper small intestinal RCmicrobiota transplant (Figure 4B), inde-
pendent of changes in plasma insulin levels (Figure 4C), and this
improvement in glucose tolerance recapitulated the gut lipid-
sensing effect seen in RC rats without a transplant (Figures 1B
and S1A). To ensure the transplant procedure per se did not
improve glucose tolerance, the microbiota of HFD rats was
transferred to HFD recipients and we found that gut Intralipid
versus saline failed to improve glucose tolerance in these rats
(Figure 4B). These data demonstrate that RCmicrobiota restores
lipid sensing to regulate glucose homeostasis in HFD rats. To
ensure the detected changes in gut lipid sensing were due to
the transfer of microbiota rather than metabolites found within
the luminal contents, the upper small intestinal microbiota was
either heat killed (Giannakis et al., 2009; Kovatcheva-Datchary
et al., 2015) or removed via filtering (Gareau et al., 2011) before
the transplant. Transfer of heat-killed or filtered luminal contents
of RC rats failed to restore gut lipid sensing in HFD-recipient
rats (Figure 4D), illustrating that restoration of upper small intes-
tinal lipid sensing in HFD rats transplanted with RC upper small
intestinal luminal contents is dependent upon the transfer of
live bacteria.
Changes in the distal intestinal microbiota correlate with
improved glucose regulation following microbiota manipulation
with pre- and probiotics (Balakumar et al., 2016; Cani et al.,
2006b; Ejtahed et al., 2012). Therefore, to assess whether
changes in the distal gut microbiota are responsible for the
improvements in upper small intestinal glucoregulatory lipid-
sensing pathways following upper small intestinal RCmicrobiota
transplantation, we transplanted the upper small intestinal mi-
crobiota of healthy RC rats directly into the colon of HFD rats
that will receive upper small intestinal Intralipid infusion during
the i.v.GTT the following day. Intralipid versus saline infusion
failed to improve glucose tolerance in HFD rats receiving a colon
RCmicrobiota transplant (Figure 4E), indicating the restoration of
upper small intestinal lipid sensing in HFD rats transplanted with
upper small intestinal RC microbiota is reliant on the normaliza-
tion of the upper small intestinal microbiota, and not the micro-
biota in the lower intestinal tract.
To further address whether HFDmicrobiota per se is sufficient
to disrupt glucoregulatory lipid-sensing pathways, upper small
intestinal microbiota obtained from 3-day HFD rats was trans-
planted into RC rats receiving gut saline or Intralipid infusion dur-
ing the i.v.GTT (Figure S4A). Intralipid failed to improve glucose
tolerance relative to a saline infusion in these rats (Figure S4B),
independent of changes in plasma insulin levels (Figure S4C),
while upper small intestinal Intralipid versus saline infusion for
50 min improved glucose tolerance in RC rats transplanted
Cell Metabolism 27, 572–587, March 6, 2018 577
Figure 5. Upper Small Intestinal Microbiota Alters Fatty Acid-Sensing Pathways that Impact GP Regulation
(A–C) The glucose infusion rate (A), glucose production (B), and glucose uptake (C) during the clamps with an oleic acid upper small intestinal infusion in HFD rats
that received an HFD microbiota transplant (n = 6), HFD rats that received an RC microbiota transplant (n = 6), RC rats that received an RC microbiota transplant
(n = 6), and RC rats that received an HFD microbiota transplant (n = 6).
(D–F) The glucose infusion rate (D), glucose production (E), and glucose uptake (F) during the clamp with a linoleic acid upper small intestinal infusion in HFD rats
that received an HFD microbiota transplant (n = 6), HFD rats that received an RC microbiota transplant (n = 6), RC rats that received an RC microbiota transplant
(n = 6), and RC rats that received an HFD microbiota transplant (n = 6).
**p < 0.01 versus RC + HFDM and HFD + HFDM rats, as determined by ANOVA with Tukey’s post hoc test. Values are shown as mean + SEM. RC, regular chow;
HFD, high-fat diet; basal, the average glucose production over the period of 60–90 min during the pancreatic (basal insulin)-euglycemic clamp; clamp, the
average glucose production from 180 to 200 min.
with RCmicrobiota (Figure S4B), and this elevation was identical
to what was seen in RC rats without a transplant receiving
an Intralipid infusion (Figures 1B and S1A). Heat-killed or filtered
luminal contents of HFD rats failed to impair gut lipid sensing in
RC-recipient rats (Figure S4D). Taken together, changes in the
upper small intestinal microbiota alter lipid-sensing-dependent
pathways to impact glucose homeostasis.
To next examine whether bidirectional changes in the upper
small intestinal microbiota impact a selective glucoregulatory
fatty acid-sensing-dependent pathway, microbiota transplant
studies were repeated in rats that underwent the gut fatty acid
infusion-pancreatic clamp studies the day after transplantation
(Figure 4A). We discovered that RC rats receiving an HFDmicro-
578 Cell Metabolism 27, 572–587, March 6, 2018
biota transplant exhibited impaired fatty acid sensing, as oleic
acid and linoleic acid failed to increase the glucose infusion
rate (Figures 5A and 5D) and lower GP (Figures 5B and 5E) rela-
tive to RC rats receiving an RC microbiota transplant. HFD rats
receiving an RC microbiota transplant responded to oleic acid
and linoleic acid infusion, leading to an increased glucose infu-
sion rate (Figures 5A and 5D) and a suppression of GP (Figures
5B and 5E) compared with the disruption in fatty acid sensing
seen in HFD rats receiving an HFD microbiota transplant.
Glucose uptake was comparable among groups (Figures 5C
and 5F).
Thus, an RCmicrobiota transplant restores themicrobiota to a
healthy condition in HFD rats, leading to the restoration of an
upper small intestinal glucoregulatory fatty acid-sensing-depen-
dent pathway.
Upper Small Intestinal Microbiota Alters ACSL3-Dependent Glucoregulatory Fatty Acid-SensingPathwayThe gut microbiota alters the expression of genes involved in
lipid metabolism in the upper and lower gut (Derrien et al.,
2011; El Aidy et al., 2013). For example, inoculation of germ-
free mice alters jejunal expression of ACSL (El Aidy et al.,
2013). Interestingly, HFD feeding lowers hepatic protein expres-
sion of the ACSL isoforms ACSL3 and ACSL4 (Bowman et al.,
2016); however, whether this effect occurs in the upper small
intestine and whether it is dependent upon diet-induced
changes in the upper small intestinal microbiota has not been
investigated. Further, whether these postulated gut microbiota-
induced changes in ACSL expression impact lipid sensing and
subsequent glucose regulation requires consideration. There
are five members of the ACSL gene family, numbered 1, 3,
4, 5, and 6 (Soupene and Kuypers, 2008). Studies exploring
mRNA expression of the genes encoding the five ACSLs in
various rat tissues found that all ACSL isoforms are expressed
in the small intestine (Bowman et al., 2016; Mashek et al.,
2006), with ACSL3 and ACSL5 being the most highly expressed
isoforms (Bowman et al., 2016). However, the protein expression
for the five ACSL isoforms has not yet been examined in the
upper small intestinal mucosa. Therefore, to begin evaluating
whether HFD-induced changes in the upper small intestinal mi-
crobiota alter upper small intestinal fatty acid-sensing pathways
via changes in ACSL expression, we first sought to determine
which isoforms are expressed in the upper small intestinal mu-
cosa and whether protein expression is altered in response to
an HFD with or without an RC microbiota transplant.
The upper small intestinal mucosa of RC, HFD, and HFD rats
with RCmicrobiota transplant was collected following the clamp
procedure. First, ACSL1, 4, 5, and 6 were detected in the upper
small intestine using brain tissue as a positive control (Figures
S5A–S5D). Expression of ACSL1, 4, 5, and 6was not significantly
altered in HFD versus RC rats (Figures S5A–S5D). In addition, the
expression of these ACSL isoforms in HFD rats that received an
upper small intestinal RC microbiota transplant was comparable
with both RC and HFD rats (Figures S5A–S5D). ACSL3 was also
detected in the upper small intestinal mucosa using brain tissue
as a positive control and heart as a negative control (Figure 6A).
However, HFD versus RC feeding consistently and significantly
reduced ACSL3 protein expression in the upper small intestinal
mucosa (Figure 6A), and this reduction was restored with an
upper small intestinal RC microbiota transplant in HFD rats
(Figure 6A).
To next investigate whether the upper small intestinal RC
microbiota transplant restores lipid sensing via upregulation of
ACSL3, we prevented ACSL3 upregulation via injection of lenti-
virus expressing either ACSL3 small hairpin RNA (shRNA) (LV-
ACSL3 shRNA) or mismatch (LV-MM). LV-ACSL3 shRNA or
LV-MM was injected into the upper small intestine 3 days prior
to the upper small intestinal RCmicrobiota transplant procedure.
The recipient rats underwent the pancreatic clamp studies the
following day. A comparable lentiviral shRNA injection protocol
has been demonstrated to knock down protein specifically in
the upper small intestine (Cote et al., 2015). We found that upper
small intestinal lipid versus saline infusion in LV-MM-injected
HFD rats with an RC upper small intestinal microbiota transplant
increased the glucose infusion rate (Figure S5E) and lowered GP
(Figure 6B), as reported previously for oleic acid and linoleic acid
sensing (Figures 5A, 5B, 5D, and 5E). Importantly, LV-ACSL3
shRNA-injected HFD rats that received an upper small intestinal
RC microbiota transplant did not respond to upper small intesti-
nal lipid infusion, as the glucose infusion rate (Figure S5E) andGP
(Figure 6B) was unaltered when compared with saline-infused
LV-ACSL3 shRNA-injected transplanted rats, while glucose up-
take was comparable among groups (Figure S5F). This inability
of upper small intestinal lipid infusion to lower GP was associ-
ated with a significant 50% reduction in protein levels of upper
small intestinal ACSL3 in LV-ACSL3 shRNA-injected HFD
transplanted rats versus LV-MM-injected HFD transplanted
rats (Figure 6C).
Since oleic acid- and linoleic acid-sensing pathways in the
upper small intestine are dependent upon GLP-1R signaling
in RC rats (Figure 2E), and that upper small intestinal infusion
of Intralipid versus saline also failed to increase glucose infu-
sion rate (Figure S5G) and lower GP (Figure S5H) in LV-
ACSL3 shRNA-injected RC rats, compared with the effects
seen in LV-MM-injected RC rats, with no changes in glucose
uptake (Figure S5I), we next investigated whether the restora-
tion of upper small intestinal ACSL3-dependent Intralipid
sensing is also GLP-1R dependent in HFD rats that received
an upper small intestinal RC microbiota transplant. We found
that, while infusion of Exendin-9 alone had no metabolic conse-
quences in these transplanted rats (Figures 6D, S5J, and S5K),
co-infusion of Intralipid with Exendin-9 completely abolished
the ability of Intralipid to increase the glucose infusion rate
(Figure S5J) and lower GP (Figure 6D) in HFD rats that received
an upper small intestinal RC microbiota transplant, with no
changes in glucose uptake (Figure S5K). Thus, transplantation
of upper small intestinal RC microbiota is sufficient to restore
an upper small intestinal ACSL3- and GLP-1R-dependent
glucoregulatory lipid-sensing pathway in HFD rats. Of interest,
given that inhibition of gut CCK-1 receptor is sufficient to
abolish the GP-lowering effect of upper small intestinal Intrali-
pid infusion as well in non-transplanted healthy rats (Cheung
et al., 2009), we put forward a working hypothesis (although
this clearly warrants future investigation) that Intralipid-induced
CCK-1 receptor and GLP-1R effect is additive in the current
experimental context.
Given that lipid sensing in HFD rats transplanted with RC
microbiota is GLP-1R dependent, and that nutrients stimulate
GLP-1 release via cell depolarization and the opening of
voltage-gated Ca2+ channels (Diakogiannaki et al., 2013; Gribble
et al., 2003; Kuhre et al., 2015; Reimann et al., 2008), we postu-
late that a 50% knock down of ACSL3 (Figure 6C) is sufficient to
prevent the threshold for the opening of Ca2+ channels to be
reached, resulting in an absence of GLP-1 release and an
inability of lipid sensing to exert glucose control in these rats.
This hypothesis is consistent with a study demonstrating that a
�40% knock down of PKCz in the rat ileum inhibits oleic acid-
induced GLP-1 release (Iakoubov et al., 2011), although the
working hypothesis warrants future investigation. Interestingly,
upper small intestinal glucose infusion increases portal active
Cell Metabolism 27, 572–587, March 6, 2018 579
Figure 6. Upper Small Intestinal Microbiota Alters an ACSL3-Dependent Fatty Acid-Sensing Pathway to Impact GP Regulation
(A) Protein expression of ACSL3 in the upper small intestinal mucosa of RC rats (n = 5), HFD rats (n = 5), and HFD rats transplanted with RC upper small intestinal
microbiota (n = 5). Brain tissue was used as a positive control; heart was used as a negative control. b-Actin and GAPDHwere used as loading controls as b-actin
is normally not detected in heart tissue. **p < 0.01 versus all other groups, as assessed by ANOVA with Tukey’s post hoc test.
(B)Glucoseproductionduring theclampofHFDrats injectedwithmismatchorACSL3 lentiviral shRNAthat receivedanuppersmall intestinalRCmicrobiota transplant
and an upper small intestinal saline (n = 5, 5), or Intralipid (n = 5, 5) infusion. **p < 0.01 versus all other groups, as assessed by ANOVA with Tukey’s post hoc test.
(C) Protein expression of ACSL3 in the upper small intestinal mucosa of mismatch (n = 6) or ACSL3 lentiviral shRNA (n = 5)-injected HFD rats that received an
upper small intestinal RCmicrobiota transplant. Brain tissue was used as a positive control; heart was used as a negative control. b-Actin and GAPDHwere used
as loading controls as b-actin is normally not detected in heart tissue. *p < 0.05 versus mismatch as determined by t test.
(D) Glucose production during the clamp of HFD rats that received an upper small intestinal RC microbiota transplant and a saline (n = 6), Intralipid (n = 6),
Exendin-9 (n = 5), or Exendin-9 + Intralipid (n = 6) upper small intestinal infusion. **p < 0.01 versus all other groups, as assessed by ANOVA with Tukey’s post hoc
test. Values are shown as mean + SEM. See also Figure S5. RC, regular chow; HFD, high-fat diet; HFD + RCM, HFD with RC microbiota transplant; ACSL3, acyl
coA synthetase 3; LV-ACSL3 shRNA, lentiviral ACSL3 shRNA; basal, the average glucose production over the period of 60–90 min during the pancreatic (basal
insulin)-euglycemic clamp; clamp, the average glucose production from 180 to 200 min.
GLP-1 levels and lowers GP in RC, but not HFD, rats during the
pancreatic clamp conditions, while co-infusion of glucose with
Exendin-9 abolishes the glucoregulatory ability of the upper
small intestinal glucose infusion in RC rats (Bauer et al., 2018).
Given that upper small intestinal fatty acid infusion similarly
lowers GP through a GLP-1R-dependent pathway in RC rats,
but failed to exert a GP-lowering effect in HFD rats (Figures 2E
and 2G), it is likely that upper small intestinal fatty acid infusion,
as conducted in the current study, also stimulates the release of
GLP-1 in RC but not HFD rats.
580 Cell Metabolism 27, 572–587, March 6, 2018
Our findings demonstrate that the restoration of upper small
intestinal ACSL3 by transplantation of RC upper small intestinal
microbiota in HFD rats is necessary to restore a glucoregulatory
lipid-dependent pathway.
Upper Small Intestinal L. gasseri AdministrationRestores Upper Small Intestinal ACSL3-DependentLipid Sensing in HFD RatsUpper small intestinal L. gasseri (from the Lactobacillus genus)
levels were reduced in response to HFD and increased to normal
Figure 7. Upper Small Intestinal Administration of L. gasseri Alters an ACSL3-Dependent Fatty Acid-Sensing Pathway via Inhibition of FXR to
Impact GP Regulation
(A) Schematic representation of the working hypothesis.
(B) Glucose production during the clamp of HFD rats pre-administered with PBS that received an upper small intestinal saline or Intralipid infusion (n = 5, 6
respectively) and HFD rats pre-administeredwith L. gasseri that received a saline or Intralipid (n = 6, 6 respectively) upper small intestinal infusion. *p < 0.05 versus
all other groups, as assessed by ANOVA with Tukey’s post hoc test.
(C) Protein expression of ACSL3 in the upper small intestinal mucosa of RC rats (n = 5), HFD rats administered with PBS (vehicle) (n = 5), HFD rats administered
with L. gasseri (n = 5), and HFD rats administered with L. gasseri followed by GW4064 (n = 5). Brain tissue was used as a positive control; heart was used as a
negative control. b-Actin and GAPDH were used as loading controls as b-actin is normally not detected in heart tissue. *p < 0.05, **p < 0.01 versus RC and HFD +
LG, as assessed by ANOVA with Tukey’s post hoc test.
(D) Glucose production during the clamp of HFD rats administeredwith PBS vehicle with or without GW4064 and infusedwith Intralipid (n = 6, 6 respectively), HFD
rats administered with L. gasseri that received 1% CMC and a saline or Intralipid infusion (n = 5, 6 respectively), or HFD rats administered with L. gasseri that
received GW4064 and a saline or Intralipid infusion (n = 6, 5, respectively). *p < 0.05 versus all other groups, as assessed by ANOVA with Tukey’s post hoc test.
Values are shown as mean + SEM. See also Figure S6. FXR, farnesoid X receptor; ACSL3, acyl CoA synthetase 3; LCFA-CoA, long-chain fatty acyl CoA; RC,
regular chow; HFD, high-fat diet; LG, L. gasseri; basal, the average glucose production over the period of 60–90 min during the pancreatic (basal insulin)-
euglycemic clamp; clamp, the average glucose production from 180 to 200 min.
levels in HFD rats that received an upper small intestinal RC
microbiota transplant (Figure 3E; Table S3). This suggests that
the increase in upper small intestinal L. gasseri could restore glu-
coregulatory fatty acid-sensing pathways and improve glucose
control in these HFD transplanted rats. L. gasseri exhibits bile
salt hydrolase activity (Rani et al., 2017), and administration of
L. gasseri probiotics alters the bile acid pool and promotes bile
acid excretion in rats (Usman and Hosono, 2001). In parallel,
the bile acid sequestrant colesevelam improves glycemic control
in diabetic humans (Beysen et al., 2012; Marina et al., 2012) and
rodents (Prawitt et al., 2011; Trabelsi et al., 2015) and inhibits in-
testinal FXR in rodents (Prawitt et al., 2011; Trabelsi et al., 2015).
Inhibition of intestinal FXR per se improves metabolic homeosta-
sis (Jiang et al., 2015; Li et al., 2013; Prawitt et al., 2011; Trabelsi
et al., 2015) in the presence of increased ACSL in the intestinal
mucosa (Li et al., 2013), while FXR activation downregulates
nutrient-stimulated GLP-1 secretion (Trabelsi et al., 2015). These
collective and correlative findings raise the possibility that
L. gasseri enhances lipid sensing via FXR inhibition and subse-
quent upregulation of ACSL3 expression in the upper small intes-
tine (Figure 7A). Of note, L. animalis was also changed in our
experimental context (Figure 3E; Table S3). However, given
that the change in L. animalis was in the opposite direction as
L. gasseri and that, to the best of our knowledge, studies to
date have not documented a role for L. animalis in bile acid ho-
meostasis, we here first tested whether L. gasseri is sufficient
to restore upper small intestinal ACSL3-dependent glucoregula-
tory lipid-sensing pathways via FXR in HFD rats.
HFD rats were administered with L. gasseri probiotics (109 col-
ony-forming units) or PBS vehicle by slowly infusing the probi-
otic over the course of 30 s via the upper small intestinal cannula
1 day prior to the pancreatic clamp studies in the same way the
upper small intestinal RC microbiota transplant was performed
(Figure 4A). During the clamps, although upper small intestinal
Intralipid infusion for 50 min had no metabolic impact relative
to a saline infusion in non-probiotic-infused (or PBS-infused)
Cell Metabolism 27, 572–587, March 6, 2018 581
HFD rats, HFD rats administered with L. gasseri probiotics ex-
hibited a restoration of upper small intestinal lipid sensing, as
upper small intestinal Intralipid versus saline infusion increased
the glucose infusion rate (Figure S6A) and decreased GP (Fig-
ure 7B) in these rats, independent of changes in glucose uptake
(Figure S6B). To investigate whether this improvement in lipid
sensing was associated with a rise in ACSL3 expression, the
upper small intestinal mucosa of HFD rats administered with
PBS vehicle or L. gasseri was collected immediately following
the saline-infused clamp procedure and ACSL3 expression
was compared with untreated RC upper small intestinal mucosal
samples. HFD rats administered with PBS vehicle (non-probi-
otic-infused) exhibited significantly reduced ACSL3 protein
expression in the upper small intestinal mucosa relative to RC
samples (Figure 7C), which is consistent with ACSL3 protein
expression in untreated HFD rats (Figure 6A). Importantly, this
reduction in ACSL3 expression was prevented with L. gasseri
probiotic administration in HFD rats (Figure 7C).
Finally, to investigate whether L. gasseri restores upper small
intestinal ACSL3-dependent lipid-sensing pathways via FXR in-
hibition, we repeated the probiotic L. gasseri experiments in the
presence or absence of FXR activation. Probiotic- (or non-probi-
otic PBS)-infused HFD rats received GW4064 (FXR agonist) or
vehicle 1% carboxymethyl cellulose (CMC) 30min after probiotic
administration. GW4060 or 1% CMC was slowly administered
over the course of 30 s via the upper small intestinal cannula,
and was administered again the following morning before
commencing the pancreatic clamp studies. First, GW4064 did
not worsen upper small intestinal lipid-sensing mechanisms in
non-probiotic-infused (i.e., PBS-infused) HFD rats compared
with non-probiotic-infused and non-GW4064 HFD rats (Figures
7D and S6C). Second, an Intralipid versus saline 50 min infusion
instead was able to increase the glucose infusion rate (Fig-
ure S6C) and lower GP (Figure 7D) in probiotic-infused HFD
rats but, importantly, this glucoregulatory effect was lost in
probiotic-infused HFD rats administered with GW4064 (Figures
7D and S6C), while glucose uptake remained unchanged
(Figure S6D). Of note, we found that GW4064 inhibited the stim-
ulatory effect of L. gasseri on upper small intestinal ACSL3
expression in these HFD rats as well (Figure 7C).
Taken together, L. gasseri enhances an upper small intestinal
ACSL3-dependent glucoregulatory lipid-sensing pathway via
FXR inhibition in HFD rodents.
DISCUSSION
We here first report that upper small intestinal oleic and linoleic
acid sensing in healthy rodents pre-absorptively increase
whole-body glucose tolerance independent of a rise in plasma in-
sulin levels and lower GP when plasma insulin levels were main-
tained at basal with a pancreatic-euglycemic clamp. Both upper
small intestinal fatty acid-sensing pathways fail to regulate
glucose tolerance and GP in lard oil-enriched HFD-fed rodents,
suggesting that HFD feeding disrupts upper small intestinal fatty
acid sensing to lower GP, leading to a disruption of whole-body
glucose homeostasis. Given that defective fatty acid sensing
arises in response to a saturated fat lard oil-enriched diet, satu-
rated palmitic and stearic acid sensing in the upper small intestine
may not share the samemetabolic effect as themonounsaturated
582 Cell Metabolism 27, 572–587, March 6, 2018
oleic and polyunsaturated linoleic acids, as currently described,
although such aworking hypothesiswarrants future investigation.
HFD reduces upper small intestinal L. gasseri levels and ACSL3
expression, while both reductions were reversed in HFD rats that
received an upper small intestinal RC microbiota transplant,
together with a restoration of the glucoregulatory ACSL3-depen-
dent lipid-sensing pathway. We further discovered that directly
administering non-transplanted HFD rats with L. gasseri probiot-
ics is sufficient to recapitulate the effect of the RC microbiota
transplant, as upper small intestinal ACSL3 expression and the
subsequent glucoregulatory function of upper small intestinal lipid
sensing are also restored in these rats. These studies together
highlight thatL.gasseridirectly impactsanACSL3-dependentglu-
coregulatory lipid-sensing pathway in the upper small intestine.
Given that probiotic supplementation with various species from
the Lactobacillus genus improve glucose parameters in rodents
and humans with diabetes (Asemi et al., 2013; Ejtahed et al.,
2012; Yadav et al., 2007), future studies are warranted to deter-
mine whether L. gasseri-induced restoration of upper small intes-
tinal sensing mechanisms could rescue glucose homeostasis in
long-term HFD-induced obese and/or diabetic rodents.
How does L. gasseri increase ACSL3 expression in the upper
small intestine? Although the mechanistic link remains largely
unknown, our preliminary data suggest that inhibition of the up-
per small intestinal bile acid receptor, FXR, could represent a
possible link. This is consistent with the fact that Lactobacillus
probiotics inhibit intestinal FXR (Degirolamo et al., 2014), and
that FXR deficiency in rodents increases intestinal ACSL expres-
sion (Li et al., 2013). Future gain- and loss-of-function genetic
experiments targeting the upper small intestinal FXR nuclear
receptor are necessary to assess the integrative role of FXR
in microbiota-induced regulation of glucoregulatory intestinal
lipid-sensing mechanisms.
Another urgent question is which bile acid(s) are involved
in L. gasseri-induced FXR inhibition? L. gasseri preferentially de-
conjugates glyco-conjugated bile acids rather than tauro-conju-
gated bile acids (Rani et al., 2017), which would lead to a drop in
glyco-conjugated bile acid with a relatively stable level of tauro-
conjugated bile acids. On one hand, deconjugation of glyco-
conjugated bile acids would result in increased excretion of
these bile acids, as deconjugation increases the hydrophobicity
of bile acids leading to increased excretion (Choi et al., 2015;
Schiff et al., 1972). In fact, similarly to other Lactobacillus species
(Degirolamo et al., 2014; Jeun et al., 2010; Kumar et al., 2011;
Lye et al., 2017), administration of L. gasseri probiotics increases
bile acid excretion in rodents (Usman and Hosono, 2001).
Consequently, Lactobacillus-induced reductions in intestinal
bile acid uptake can reduce activity of the bile acid receptor
FXR in the intestine (Degirolamo et al., 2014). On the other
hand, tauro-conjugated bile acids, such as tauro-b-muricholic
acid, inhibit FXR and improve glucose homeostasis in obese
rats (Li et al., 2013; Sayin et al., 2013). Thus the potential relative
increase in tauro-conjugated bile acids could also contribute to a
L. gasseri-induced suppression of FXR. Nonetheless, assessing
bile acids as links between L. gasseri and ACSL3-dependent
lipid-sensing pathways as well as how microbiota transplanta-
tion affects bile acid pool warrant future investigations.
Microbiota changes in the large intestine and feces correlate
with changes in host metabolism (Forslund et al., 2015; Karlsson
et al., 2013; Le Chatelier et al., 2013; Qin et al., 2012; Ridaura
et al., 2013) and transplantation of large intestinal or fecal micro-
biota from HFD obese rodents impairs glucose homeostasis in
recipient rodents (Kovatcheva-Datchary et al., 2015; Parseus
et al., 2017; Perry et al., 2016; Ridaura et al., 2013). In parallel,
administration of probiotics improves glucose homeostasis in
diabetic rodents in association with changes in large intestinal
and fecal microbiota composition (Balakumar et al., 2016; Cani
et al., 2006b; Kovatcheva-Datchary et al., 2015; Neyrinck
et al., 2012; Zhou et al., 2008), together suggesting that changes
in large intestinal microbiota affect glucose homeostasis. These
studies clearly did not (and could not) rule out that upper small
intestinal microbiota does (or does not) impact metabolic ho-
meostasis. Instead, we here report that the upper small intestinal
RC microbiota transplant rescues upper small intestinal lipid-
sensing pathways in HFD-recipient rats via specific changes in
the upper small intestinal microbiota, rather than changes in
the colonic tract. However, our studies are in no way implying
that direct HFD-induced changes in colonic microbiota do not
impact glucose homeostasis as well. Taken together, we pro-
pose a potential parallel role of the distal and upper small intes-
tinal microbiota in glucose homeostasis.
In fact, metformin has been documented to alter both distal in-
testinal (de la Cuesta-Zuluaga et al., 2017; Forslund et al., 2015;
Shin et al., 2014;Wu et al., 2017) and upper small intestinalmicro-
biota (Bauer et al., 2018) in parallel to improvements in glucose
homeostasis. While HFD feeding lowers upper small intestinal
L. gasseri levels (Figure 3) (Bauer et al., 2018), transplantation
of metformin-treated microbiota into the upper small intestine
of HFD-recipient rats does not alter L. gasseri levels (in contrast
to what is currently described for the RC microbiota transplant
in HFD rats (Figure 3)). Transplantation of metformin-treated mi-
crobiota instead increases Lactobacillus salivarius in parallel to
a restoration of an upper small intestinal SGLT1-dependent glu-
coregulatory glucose-sensing pathway (Bauer et al., 2018). Given
that L. gasseri activates an ACSL3-dependent glucoregulatory
lipid-sensing pathway via FXR inhibition in the upper small intes-
tine (Figure 7), and that L. salivarius, like L. gasseri, exhibits bile
salt hydrolase activity (Wang et al., 2012; Xu et al., 2016), which
could impact the bile acid pool and subsequent FXR activity,
we propose (which clearly warrants future investigation) that
upper small intestinal FXR could be a common pathway that links
members of the Lactobacillus genus, such as L. gasseri and
L. salivarius, with nutrient-sensing mechanisms to exert glucore-
gulatory effects in obesity and diabetes.
In summary, L. gasseri probiotic administration in HFD rats, or
transplantation of RC upper small intestinal microbiota that in-
creases upper small intestinal L. gasseri levels in HFD-recipient
rats, enhances an upper small intestinal ACSL3-dependent glu-
coregulatory lipid-sensing pathway in rodents. These findings
strengthen the claim on the causative glucoregulatory role of
the gut microbiota and highlight L. gasseri as an important regu-
lator of nutrient sensing mechanisms in the upper small intestine
to exert metabolic benefits.
Limitations of StudyThe first key limitation of our study is that the current working hy-
pothesis has yet to be tested in chronic obese and/or diabetic
animalmodels aswell as in healthy, obese, and diabetic humans.
A second key limitation is that the glucoregulatory role of ACSL
isoforms other than ACSL3, as well as the definitive glucoregula-
tory role of the bile acids, has not been investigated in the current
as well as chronic obese and/or diabetic models. Lastly, the
glucoregulatory role of the members of the Lactobacillus genus
other than L. gasseri has yet to be assessed.
STAR+METHODS
Detailed methods are provided in the online version of this paper
and include the following:
d KEY RESOURCES TABLE
d CONTACT FOR REAGENT AND RESOURCE SHARING
d EXPERIMENTAL MODEL AND SUBJECT DETAILS
B Animals
d METHOD DETAILS
B Surgical Procedures
B Virus Injection
B High-fat Diet Model
B Intravenous Glucose Tolerance Test
B Rat Pancreatic (Basal Insulin) Clamp Procedure
B Mouse Pancreatic (Basal Insulin) Clamp Procedure
B Fatty Acid Preparation for Upper Small Intestinal In-
fusions
B Upper Small Intestinal Infusions
B Microbiota Transplant
B Microbiota Heat-Shock
B Microbiota Filter
B Lactobacillus Gasseri Administration
B GW4064 Administration
B Genomic DNA Extraction and 16S rRNA Gene
Sequencing
B Sequence Processing and Data Analysis
B Tissue Collection and Western Blotting
B Biochemical Analysis
d QUANTIFICATION AND STATISTICAL ANALYSIS
SUPPLEMENTAL INFORMATION
Supplemental Information includes six figures and three tables and can be
found with this article online at https://doi.org/10.1016/j.cmet.2018.01.013.
ACKNOWLEDGMENTS
This work was supported by a Canadian Institutes of Health Research (CIHR)
Foundation Grant to T.K.T.L. (FDN-143204). P.V.B. is supported by an Ontario
Graduate Scholarship and a Banting and Best Diabetes Center Graduate Stu-
dentship. F.A.D. was aBanting Fellow. T.M.Z.W. is supported by aBanting and
Best Diabetes Center Post-Doctoral Fellowship. H.J.D. is supported by a CIHR
and a Diabetes Canada post-doctoral fellowship. B.A.R. was a Vanier Scholar.
T.K.T.L. holds the John KitsonMcIvor (1915–1942) Endowed Chair in Diabetes
Research and the Canada Research Chair in Obesity at the Toronto General
Hospital Research Institute and the University of Toronto.
AUTHOR CONTRIBUTIONS
P.V.B. conducted and designed the experiments, performed the data ana-
lyses, and wrote the manuscript. F.A.D., T.M.Z.W., and H.J.D. assisted with
the experiments and edited the manuscript. B.A.R., A.P., M.R., and C.A.O. as-
sisted with the experiments. T.K.T.L. supervised the project, designed the ex-
periments, and edited the manuscript.
Cell Metabolism 27, 572–587, March 6, 2018 583
DECLARATION OF INTERESTS
The authors declare no competing interests.
Received: May 15, 2017
Revised: November 9, 2017
Accepted: January 22, 2018
Published: March 6, 2018
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Cell Metabolism 27, 572–587, March 6, 2018 587
STAR+METHODS
KEY RESOURCES TABLE
REAGENT or RESOURCE SOURCE IDENTIFIER
Antibodies
GAPDH antibody Cell Signaling Biotechnology Cat# 2118S
b-actin antibody Sigma Aldrich Cat# A1978
ACSL1 antibody Cell Signaling Technology Cat# 4047
ACSL3 antibody Santa Cruz Biotechnology Cat# sc-166374
ACSL4 antibody Abcam Cat# ab155282
ACSL5 antibody Novus Biologicals Cat# NPB1-59645
ACSL6 antibody Abcam Cat# ab154094
Bacterial and Virus Strains
ACSL3 shRNA (r) Lentiviral Particles Santa Cruz Cat# sc-270649-V
Control shRNA Lentiviral Particles-A Santa Cruz Cat# sc-108080
Lactobacillus gasseri Lauer and Kandler (ATCC 33323) American Type Culture Collection Cat # 33323
Chemicals, Peptides, and Recombinant Proteins
D-(+)-Glucose solution Sigma Aldrich Cat# G8769
[3-3H] Glucose Perkin Elmer Part# NEC042V250UC
Oleic acid Sigma Aldrich Cat# O1008
Linoleic acid Sigma Aldrich Cat# L1376
L-a-phosphatidylcholine Sigma Aldrich Cat# P7443
Sodium salt of taurcholic acid Sigma Aldrich Cat# 86339
Intralipid Sigma Aldrich Cat# I141
MK-329 Tocris Bioscience Cat# 2304
Exendin-9 Tocris Bioscience Cat# 2081
Tetracaine Sigma Aldrich Cat #T7383
Lactobacilli MRS Broth (ATCC Medium 416) Fischer Scientific Cat# DF0882170
GW4064 Sigma Aldrich Cat# G5172
Sodium carboxymethyl cellulose Sigma Aldrich Cat# 419273
Mutaniolysin Sigma Aldrich Cat# M9901
RNase A Qiagen Cat# 19101
Tris-HCl Roche Cat# 10812846001
EGTA Sigma Aldrich Cat# E3889
EDTA Sigma Aldrich Cat# E9884
Nonidet P40 Roche Cat# 11332473001
Sodium orthovanadate Sigma Aldrich Cat# S6508
Sodium fluoride Sigma Aldrich Cat# S7920
Dithiotritol Sigma Aldrich Cat# D9779
Protease inhibitor cocktail Roche Cat# 11836153001
HR series NEFA-HR color reagent A Wako Diagnostics Cat# 999-34691
HR series NEFA-HR solvent A Wako Diagnostics Cat# 995-34791
HR series NEFA-HR color reagent B Wako Diagnostics Cat# 991-34891
HR series NEFA-HR solvent B Wako Diagnostics Cat# 993-35191
NEFA standard solution Wako Diagnostics Cat# 276-76491
Wako NEFA linearity set Wako Diagnostics Cat# 997-76491
Critical Commercial Assays
Rat Insulin Radioimmunoassay EMD Millipore Cat# RI-13K
Pierce 660 nm Protein Assay Thermo Fischer Scientific Cat# 22660
DNA Clean and Concentrator Kit Zymo Research Cat# D4003T
(Continued on next page)
e1 Cell Metabolism 27, 572–587.e1–e6, March 6, 2018
Continued
REAGENT or RESOURCE SOURCE IDENTIFIER
Experimental Models: Organisms/Strains
Sprague Dawley Rats Charles River Laboratories Strain# 400
C57BL6/J Mice Jackson Laboratories Strain# 000664
Software and Algorithms
QIIME bioinformatics pipeline Open Source qiime.org
R programming language Open Source RRID: SCR_001905
GraphPad Prism 7 GraphPad Software www.graphpad.com
CONTACT FOR REAGENT AND RESOURCE SHARING
Further information and requests for resources and reagents should be directed to andwill be fulfilled by the Lead Contact, Tony Lam
EXPERIMENTAL MODEL AND SUBJECT DETAILS
AnimalsEight-week old adult male Sprague-Dawley rats (280-300g) were obtained from Charles River Laboratories (Montreal, Quebec,
Canada). Eighteen-week-old adult male C57/BL/6 mice (25-30g) were obtained from Jackson Laboratories (Bar Harbor, Maine,
USA). Sex-differences were not examined in the current manuscript. Both rats and mice were housed individually and maintained
on a standard light-dark cycle with ad libitum access to chow (Teklad Diet #7002, Harlan Laboratories) (Table S1) and water. All
animal protocols were reviewed and approved by the Toronto General and Western Animal Care Committee at UHN.
METHOD DETAILS
Surgical ProceduresAnimals were given at least 6 days to acclimatize before surgeries were performed. Rat surgeries were performed 4 days prior to
intravenous glucose tolerance tests (ivGTT) and clamp experiments. An upper small intestinal catheter was placed 6 cm distal to
the pyloric sphincter to target the lower duodenum and upper jejunum (between 6 and �12 cm distal to the pyloric sphincter) during
a 50-min upper small intestinal infusion, while carotid artery and jugular vein cannulations were performed for infusion and sampling
during the clamp. Two to three days before the mouse pancreatic clamp studies, a catheter was placed in the upper small intestine
(1.5-2 cm distal to the pyloric sphincter) to target the lower duodenum and upper jejunum, while a catheter was placed in the jugular
vein for infusion purposes and tail sampling was performed during the clamp studies. Following surgery, both rats and mice were
housed individually and maintained on a standard light-dark cycle with ad libitum access to food and water. Food intake and
body weight was monitored to ensure recovery from surgery, and rats that did not recover to 90% of their baseline body weight
were excluded from the study. Rats were randomly designated into treatment groups prior to experiments and no blinding was
done during the experimental procedures described below.
Virus InjectionA subset of rats received an upper small intestinal lentiviral injection prior to the insertion of the intestinal cannula as described (Cote
et al., 2015; Kokorovic et al., 2011). Briefly, the upper small intestine was elevated from 6 to 12 cm distal to the pyloric sphincter and
was ligated with sutures at both ends to restrict outward flow of virus and inward flow of intestinal fluids. The elevated intestinal
portion was first flushed with 0.2-0.5 mL of saline via a 23-gauge needle inserted right below the 6 cm ligation, and then 0.2 mL
of the lentivirus expressing mismatch or ACSL3 shRNA (both at 1.0 x 106 IFU; 20 mL was diluted into a total volume of 0.2 mL for
injection) (Santa Cruz, CA, USA) was administered via the 23-gauge needle. After 20 min, ligations sutures were removed and the
intestine was flushed with saline. A catheter was then inserted in the site of the virus injection and vascular cannulations were per-
formed as described above.
High-fat Diet ModelRats were placed on a lard oil-enriched high fat diet (HFD; TestDiet #571R, PurinaMills, IN, USA) (Table S1) and allowed to overeat for
three days before the ivGTT or pancreatic clamp procedure, which results in hyperphagia (Figures S1D and S2J) and upper small
intestinal lipid sensing defects (Breen et al., 2011; Cheung et al., 2009; Rasmussen et al., 2012) but not obesity (Figures S1E and
S2K). The same 3-day HFD-induced hyperphagic response has been documented by others to be sufficient to induce insulin and
leptin resistance but insufficient to increase body weight (Morgan et al., 2004; Scherer et al., 2012; Thaler et al., 2012), thus repre-
senting an early onset HFD-induced obese model. Under rare circumstances when rats were not hyperphagic they were excluded
from the study.
Cell Metabolism 27, 572–587.e1–e6, March 6, 2018 e2
Intravenous Glucose Tolerance TestExperiments were performed in overnight-fasted rats (16-18 hr) 4 days after surgery. Basal blood samples were obtained in
conscious, unrestrained rats immediately before beginning the gut infusion (0.01 mL/min), which began at t = -15 min and was main-
tained until the end of the experiment at t = 35 min. At t = 0 min blood samples were obtained and an intravenous bolus of glucose
(20% glucose, 0.25 g/kg) was injected into the jugular vein and flushed with saline. Blood was collected via the carotid arte. ry cath-
eter tomeasure plasma glucose and insulin levels for 35min following the glucose injection, as previously described (Yue et al., 2016).
Rat Pancreatic (Basal Insulin) Clamp ProcedureThe clamp was performed as described previously (Cheung et al., 2009; Wang et al., 2008; Yue et al., 2016). After a 4-6 hr fast, a
primed continuous infusion of [3-3H]-glucose (40 mCi bolus; 0.4 mCi min�1; Perkin Elmer, Woodbridge, ON, Canada) was given
from t = 0 to t = 200 min (start to end of the experiment) through an intravenous catheter to assess glucose kinetics based on the
tracer dilution methodology. Starting at t = 90min and continuing to the end of the experiment (t = 200), a pancreatic clamp was con-
ducted through infusion of insulin (1.2mU kg�1 min�1) and somatostatin (3 mg kg�1min�1) to inhibit endogenous insulin and glucagon
secretion. Somatostatin-14was used, which has been shown to have a veryminor inhibitory effect on GLP-1 release when compared
with somatostatin-28 (Brubaker, 1991; Chisholm and Greenberg, 2002; Hansen et al., 2000). Furthermore, upper small intestinal
glucose infusion was shown to stimulate GLP-1 release during the pancreatic basal insulin clamp with the same dose of somato-
statin-14 (Bauer et al., 2018), suggesting this dose of somatostatin-14 does not inhibit GLP-1 release under these conditions.
Between t = 120 and t = 200, blood samples were taken every 10 min to determine the rate of an exogenous 25% glucose infusion
needed to maintain basal glucose levels (averaged from t = 60-90). At t = 150 min, the upper small intestinal infusion (0.01 mL/min)
was started and continued until the end of the experiment (t = 200). To determine insulin levels and specific activity of [3-3H]-glucose,
plasma samples were taken every 10 min during the basal period (t = 60-90) and the gut infusion period (t = 150-200). Upon comple-
tion of the experiment rats were anaesthetized and upper small intestinal microbiota luminal samples (between 6 and 15 cm distal to
the pyloric sphincter), as well asmucosal scrapings (between 6 and 10 cmdistal to the pyloric sphincter), were collected, snap-frozen
in liquid nitrogen and stored at -80�C until use.
Mouse Pancreatic (Basal Insulin) Clamp ProcedureMice were fasted for 4-6 hr prior to experimentation. Through an intravenous catheter, a primed-continuous intravenous infusion
of [3-3H]-glucose (1 mCi bolus; 0.1 mCi/min; Perkin Elmer, Woodbridge, ON, Canada) was given from t = 0 to t = 170 min (start to end
of the experiment) to assess glucose kinetics based on the tracer dilution methodology. Starting at t = 60 and continuing to the end of
theexperiment (t=170), a pancreaticclampwasconducted through infusionof insulin (1.4mU/kg/min) andsomatostatin (8.3mg/kg/min).
Blood samples were taken via tail sampling every 10 min to determine if an exogenous 10% glucose infusion was needed to maintain
basal glucose levels (averaged from t = 50-60) between t = 60 to t = 170.Upper small intestinal infusions (2mL/min) of oleic acid or linoleic
acid (4 x 10-3 kcal/min) were performed from t = 120 to t = 170. To determine specific activity of [3-3H]-glucose levels, plasma samples
were taken every 10 minutes during the basal period (t = 50-60) and the upper small intestinal infusion period (t = 120-170).
Fatty Acid Preparation for Upper Small Intestinal InfusionsOleic acid (99% purity; Sigma, St. Louis, MO) and linoleic acid (99% purity; Sigma) were administered at 2 kcal/mL to mimic the con-
centration of the Intralipid infusate, which has been shown to lower glucose production when infused directly into the upper small
intestine at 0.01 mL/min (Wang et al., 2008). In addition, this dose of oleic acid and linoleic acid (total of 1 kcal delivered) has
been shown to inhibit food intake in rats when infused into the upper small intestine (Phifer and Berthoud, 1998; Woltman et al.,
1995). Fatty acid solutions were prepared as previously described (Woltman et al., 1995). Briefly, fats were emulsified in phosphate
buffered saline (PBS; 115 mM NaCl, 16.5 mM NaH2PO4, 6.75 mM Na2HPO4, and 5 mM KCl; pH 6.4) containing 0.1% wt/vol
(1.24 mmol/mL) lecithin (L-a-phosphatidylcholine, 99% pure; Sigma) and 1% wt/vol (17.5 mmol/mL) sodium taurocholate (sodium
salt of taurcholic acid, 98% pure; Sigma). These bile acid concentrations are comparable to levels detected in the upper small intes-
tine of humans in postprandial (90min after a standardizedmeal) conditions [1.0 – 2.5 mmol/mL (lecithin) and 12 – 17 mmol/mL (sodium
taurocholate)] (Clarysse et al., 2009; Mansbach et al., 1975). Solutions were emulsified until homogenous with an Autotune Series
High Intensity Ultrasonic Processor.
Upper Small Intestinal InfusionsThe following substances were infused into the upper small intestine at a rate of 0.01 mL/min as described: (1) saline, (2) PBS + bile
salts (PBS with lecithin and sodium taurocholate) (3) Intralipid (2 kcal/mL) (4) Oleic acid (2 kcal/mL; in PBS and bile salts) (5) Linoleic
acid (2 kcal/mL; in PBS and bile salts), (5) MK-329 (0.08 mg/mL; Tocris Bioscience), (6) Exendin-9 (15 mg/mL; Tocris Bioscience) and
(6) tetracaine (1 mg/mL; Sigma). The dose of Intralipid (1 kcal delivered over 50 min) was chosen to ensure the effects observed were
in the pre-absorptive state (Greenberg et al., 1995; Wang et al., 2008). The dose used for oleic acid and linoleic acid were chosen to
mimic the Intralipid dose (1 kcal). In addition, this dose of oleic acid and linoleic acid (total of 1 kcal) has been shown to inhibit food
intake in rats (Phifer and Berthoud, 1998; Woltman et al., 1995). The dose of MK-329 was previously shown to inhibit lipid sensing in
the upper small intestine (Cheung et al., 2009). The dose of Exendin-9 has been shown to inhibit the effects of ileal fatty acid sensing
(Zadeh-Tahmasebi et al., 2016). The dose of tetracaine was previously shown to inhibit the glucose production-lowering effects of an
upper small intestinal Intralipid infusion (Wang et al., 2008).
e3 Cell Metabolism 27, 572–587.e1–e6, March 6, 2018
Microbiota TransplantDonor rats were anaesthetized after a 4-6 hr fast and the upper small intestinal luminal contents were removed from the upper small
intestine (between �6-15 cm distal to the pyloric sphincter to collect a sufficient amount of luminal contents for transplantation). The
luminal contents were homogenized and diluted 1:4 in PBS and 0.5mL of the luminal contents were slowly infused (over the course of
30 seconds) into 4-6 hr-fasted recipient rats via the upper small intestinal gut line to target the lower duodenum and upper jejunum. To
validate that the transplant effectively altered the upper small intestinal microbiota composition, the upper small intestinal luminal
contents of anaesthetized recipient rats obtained from �6-15 cm distal to the pyloric sphincter was collected immediately after
the infusion experiments, snap frozen in liquid nitrogen and stored at -80�C for subsequent 16S rRNA gene sequencing (see below).
For the colonic microbiota transplant, the upper small intestinal contents were removed and prepared for infusion in the sameway as
the upper small intestinal microbiota transplant. The luminal contents were then transplanted into recipient rats via a colonic cannu-
lation located 2 cmdistal to the cecum. Recipient rats were subjected to the ivGTT or the basal insulin euglycemic clamp the following
day. Recipient rats undergoing the ivGTT were immediately fasted following the transplant procedure (16-18 hr fast). Recipient rats
undergoing the clampswere given their original diet (the diet being consumed prior to transplantation) and fasted for 4-6 hr prior to the
clamp procedure.
Microbiota Heat-ShockBefore transferring the upper small intestinal luminal contents to the recipient rat, bacteria was heat-killed by incubation at 95-100�Cfor two 5 min intervals. The heat-treated samples were cultured on LB agar plates at 37�C for 96 hr to prove that no viable organisms
remained.
Microbiota FilterTo obtain bacteria-free samples, luminal contents were filtered through 0.2 mm (Millex) filters (Gareau et al., 2011) before being trans-
ferred to recipient rats. The filtered samples were cultured on LB agar plates at 37�C for 96 hr to prove that no viable organisms
remained.
Lactobacillus Gasseri AdministrationLactobacillus gasseri Lauer and Kandler (ATCC 33323) was freshly prepared for each administration. Briefly, the probiotic was
grown overnight in Lactobacilli MRS Broth (ATCC Medium 416) under anaerobic conditions at 37�C the evening prior to adminis-
tration. The following day, 109 colony-forming units (cfu) were dissolved in a total volume of 0.5 mL of PBS and slowly infused (over
the course of 30 seconds) into 4-6 hr-fasted recipient rats via the upper small intestinal gut line to target the lower duodenum and
upper jejunum. Control HFD-fed rats received 0.5 mL of vehicle PBS. Basal insulin euglycemic clamps were performed the following
day after a 4-6 hr fast. The Lactobacillus gasseri probiotic dose (109 cfu) was shown to increase bile acid excretion in male Sprague
Dawley rats (Usman and Hosono, 2001). In addition, a comparable dose (5 x 109 cfu) of a probiotic mixture containing a variety of
species from the Lactobacillus genus increased bile acid excretion and decreased small intestinal FXR expression in mice (Degir-
olamo et al., 2014).
GW4064 AdministrationA subset of Lactobacillus gasseri-infused and control PBS-infused HFD rats were administered with the FXR agonist, GW4064
(30mg/kg; Sigma; dissolved in 1% carboxymethyl cellulose; administered via the gut line over the course of 30 seconds and followed
by a saline gut line flush), 30 min following the Lactobacillus gasseri or PBS administration and again the next morning after a 4-6 hr
fast (immediately prior to the basal insulin-euglycemic clamps). Control HFD-fed rats received 1%carboxymethyl cellulose. The dose
of GW4064 (30 mg/kg) was chosen based on previous work reporting an inhibition of glucose-stimulated GLP-1 release in response
to GW4064 (30 mg/kg) administered via gavage for 5 days (Trabelsi et al., 2015). In addition, oral GW4064 was shown to inhibit
probiotic-induced increased bile acid excretion after two treatments at a comparable dose (45 mg/kg) (Degirolamo et al., 2014).
Lactobacillus gasseri-infused HFD rats were initially given a single dose of GW4064 (30 mg/kg) 30 min following the probiotic admin-
istration. However, we found that a single GW4064 treatment only partially blocked the restoration of upper small intestinal lipid
sensing in Lactobacillus gasseri-infused HFD rats during the pancreatic clamps (Gut Lipid-infused, GP was 8.9 mg kg�1 min�1
(n = 1) vs. Gut saline-infused, GP was 11.4 mg kg�1 min�1 (n = 1)). Given that the effect of GW4064 on glucose-stimulated GLP-1
release and bile acid excretion occurred following daily treatment for 5 and 2 days, respectively (Degirolamo et al., 2014; Trabelsi
et al., 2015), we next administered the same dose of GW4064 (30 mg/kg) immediately following the Lactobacillus gasseri-infusion
and again the next morning prior to the clamp. We found that two treatments with GW4064 (30 mg/kg) blocked the restorative effect
of Lactobacillus gasseri administration on upper small intestinal lipid sensing, with no metabolic impact in non-probiotic-infused
(PBS-infused) HFD rats (Figure 7D).
Genomic DNA Extraction and 16S rRNA Gene SequencingUpper small intestinal luminal contents obtained from between �6-15 cm distal to the pyloric sphincter were collected from rats
immediately following upper small intestinal saline-infused basal insulin-euglycemic pancreatic clamps. Genomic DNA extraction
and purification was performed as described previously (Whelan et al., 2014). Intestinal luminal contents were added to a 2mL plastic
screw top tube containing 0.2 g of 0.1 mm glass beads (MO BIO laboratories, Inc.). Subsequently, 800 mL of 200 mM NaPO4 (pH 8)
Cell Metabolism 27, 572–587.e1–e6, March 6, 2018 e4
and 100 mL of guanidine thiocyanate-EDTA-N-lauroyl sarcosine were added to the tube and homogenization was performed for 3min
with a bench-top bead-based homogenizer (Minilys personal homogenizer). For the first enzymatic lysis step, 50 mL of mutanolysin
(Sigma-aldrich, 10 U/mL), 10 mL of RNase A (Qiagen, 10 mg/mL) and 100 mL of 5M NaCl were added to each sample. The samples
were vortexed and incubated at 65�C (water bath) for 1 hr. After incubation, the tubes were spun at maximum speed for 5 min in a
bench-top centrifuge and 900 mL of the supernatant was removed and transferred to a 2 mL tube containing 900 mL of phenolchloro-
form-isoamyl alcohol (25:24:1). After vortexing the tubes for 10 seconds (shear DNA), they were again spun at maximum speed in the
bench-top centrifuge for 10 min. After centrifugation, the top layer was carefully transferred to a 1.5 mL microfuge tube. DNA clean
and concentrator-25 kit (Zymo Research) was used for purifying the DNA, where DNAwas eluted from the columnwith 50 mL of water
and the samples were diluted to a final concentration of 20 ng/mL. DNA samples were quantified using Nanodrop spectrophotometer
(NanoDrop 2000c, Thermo Scientific) and isolated DNA was stored at -20�C.PCR amplification of the V3 region of the 16S rRNA gene was performed as previously described (Bartram et al., 2011) with the
following modifications: a 50 mL reaction containing 1.25 mM MgCl2, 2.5 mM of each dNTP, 100 nM of each barcoded primer,
and 1.25 U Taq polymerase. Amplifications were carried out in triplicate, where the amplified product was purified by separation
with agarose gel electrophoresis and gel extraction. PCR conditions consisted of an initial denaturation at 94�C for 2 min followed
by 30 cycles at 94�C for 30 seconds, 50�C for 30 seconds and a final elongation at 72�C for 10 min. Purified PCR products were
sequenced using the Illumina MiSeq platform at the McMaster Genome Facility (Hamilton, ON, Canada).
Sequence Processing and Data AnalysisPCR products were sequenced using Illumina MiSeq with paired-end reads. 16S rRNA gene sequencing was completed as previ-
ously described (Whelan et al., 2014). Custom Perl scripts were developed in-house to process the sequences. First, Cutadapt
was used to trim these sequences to the V3 region, removing any sequences surpassing this region. Next, sequences were aligned
with their pair using PANDAseq (Masella et al., 2012). During this alignment any mismatches or ambiguous bases were culled. Oper-
ational taxonomic units (OTUs) were picked using AbundantOTU and as described previously (Ye, 2011) with a clustering cut-off of
97%. Taxonomy of the resultant OTUs was assigned via comparison of a representative sequence of the unit to the GreenGenes
reference database (4 February 2011 release) (DeSantis et al., 2006) using the Ribosomal Database Project (RDP) classifier
(Wang et al., 2007). Summaries of the relative abundances of taxonomies, as well as beta and alpha diversity measurements
were calculated using Quantitative Insights Into Microbial Ecology (QIIME, v1.9.1) (Caporaso et al., 2010). The rarefaction depth
was 10,000 sequences/sample. Three-dimensional Principal Coordinate Analysis plots were visualized using Emperor (Vazquez-
Baeza et al., 2013). The significance of clustering was determined by passing the UniFrac distance matrices through QIIME using
Adonis and ANOSIM non-parametric statistical methods. LefSe (Linear Discriminant Analysis with Effect Size) analyses were per-
formed on the website https://huttenhower.sph.harvard.edu/galaxy/ (Segata et al., 2011). The differential features were identified
at the Phylum (p), Class (c), Order (o), Family (f), and Genus (g) levels. The alpha value for the factorial Kruskal-Wallis test among
classes was <0.05 and the threshold on the logarithmic LDA score for discriminative features was >2.0. For group comparisons,
the one-way ANOVA test was used with a Tukey’s multiple comparisons test. Statistical analyses were performed using GraphPad
Prism. A p value <0.05 was considered significant.
Tissue Collection and Western BlottingA section of the upper small intestine �6-10 cm distal to the pyloric sphincter, containing both lower duodenum and upper jejunum,
was removed from anaesthetized rats immediately following the infusion experiments. The upper small intestinal mucosa was sepa-
rated from the smooth muscle and quickly placed in liquid nitrogen. The tissues were lysed on ice with a handheld homogenizer in a
lysis buffer containing 50 mM Tris-HCl (pH 7.5), 1 mM EGTA, 1 mM EDTA, 1% (w/v) Nonidet P40, 1 mM sodium orthovanadate,
50 mM sodium fluoride, 5 mM sodium pyrophosphate, 0.27 M sucrose, 1 mM Dithiotritolo (DTT) and protease inhibitor cocktail
(Roche). The protein concentration of homogenized tissues was determined using the Pierce 660 nm protein assay (Thermo Sci-
entific). 50 mg of tissues lysates were subject to electrophoresis on 10% acrylamide gels and transferred to nitrocellulose mem-
branes. The membranes were incubated for 1 hr with blocking buffer (5% bovine serum albumin in TBS-T), followed by incubation
in primary antibody 2 hr at 4�C. b-actin (Sigma, #A1978) and GAPDH (Cell Signaling, #2118S) were used as loading controls. The
antibodies were prepared in 5% bovine serum albumin in TBS-T at the following dilutions: 1:1000 for ACSL1 (#4047, Cell Signaling
Technology), 1:250 for ACSL3 (sc-166374, Santa Cruz Biotechnology), 1:10000 for ACSL4 (ab155282, Abcam), 1:1000 for ACSL5
(NPB1-59645, Novus Biologicals), and 1:10000 for ACSL6 (ab154094, Abcam). The blots were then washed three times in TBS-T
and incubated with a horseradish peroxidase (HRP)-linked secondary antibody (1:4000 dilution in 5% skim milk) for 2 hr. Blots were
washed 5 times in TBS-T and protein expression was detected using an enhanced chemiluminescence reagent (Clarity Western
ECL Blotting Substrate, Bio-Rad). Immunoblots were imaged using a MicroChemi chemiluminescent imaging system (DNR Bio-
Imaging Systems).
Biochemical AnalysisPlasma insulin concentrations were measured using a radioimmunoassay (Linco Research, St Charles, MO) and plasma free fatty
acid concentrations were measured by an enzymatic assay (Wako Pure Chemical Industries, Osaka, Japan).
e5 Cell Metabolism 27, 572–587.e1–e6, March 6, 2018
QUANTIFICATION AND STATISTICAL ANALYSIS
The sample size for each group was chosen based on study feasibility and previously published experiments. Data from all groups
showed normal variance. Therefore, the results were analyzed using unpaired Student’s t test when analyzing statistical difference
between two groups.When comparisons weremade acrossmore than two groups, ANOVAwas performed and if significant this was
followed by Tukey’s post hoc test. Measurements that were taken repeatedly over time were compared using repeated measures
two-way ANOVA; if the time and treatment interaction between groups was found to be significant Tukey’s multiple comparisons
test was used to determine the statistical significance at specific time points between groups. p value < 0.05 was considered
statistically significant. For clamp experiments, the time period of 60-90 min was averaged for the basal condition and the period
of 180-200 min was averaged for the clamp condition.
Cell Metabolism 27, 572–587.e1–e6, March 6, 2018 e6