Go back to previous article. Sign in. Learning Objectives Describe the role played by the small intestine in the absorption of nutrients. Key Points Digested food is able to pass into the blood vessels in the wall of the small intestine through the process of diffusion.

The inner wall, or mucosa, of the small intestine is covered in wrinkles or folds called plicae circulares that project microscopic finger-like pieces of tissue called villi, which in turn have finger-like projections known as microvilli. Each villus transports nutrients to a network of capillaries and fine lymphatic vessels called lacteals close to its surface.

Key Terms villi : Tiny, finger-like projections that protrude from the epithelial lining of the intestinal wall. plicae circulares : These circular folds known as the valves of Kerckring or the valvulae conniventes are large, valvular flaps that project into the lumen of the bowel.

diffusion : The act of diffusing or dispersing something, or the property of being diffused or dispersed; dispersion. EXAMPLES Examples of nutrients absorbed by the small intestine include carbohydrates, lipids, proteins, iron, vitamins, and water. The Small Intestine The small intestine is the part of the gastrointestinal tract between the stomach and the large intestine where much of the digestion of food takes place.

Absorption of the majority of nutrients takes place in the jejunum, with the following notable exceptions: Iron is absorbed in the duodenum. In addition, the intestine absorbs water and electrolytes, thus playing a critical role in maintenance of body water and acid-base balance.

It's probably fair to say that the single most important process that takes place in the small gut to make such absorption possible is establishment of an electrochemical gradient of sodium across the epithelial cell boundary of the lumen. This is a critical concept and actually quite interesting.

Also, as we will see, understanding this process has undeniably resulted in the saving of millions of lives. To remain viable, all cells are required to maintain a low intracellular concentration of sodium. Enterocytes in the small intestine absorb large amounts of sodium ion from the lumen, both by cotransport with organic nutrients and by exchange with protons.

To compare cell types in the human ileum, colon, and rectum, the 14, cells were pooled together, and their transcriptome profiles were subjected to unsupervised graph-based clustering Butler et al. Based on previously reported cell markers Fig.

S2 A and Table S1 and other intestinal single-cell sequencing results Grün et al. Using the same cell markers Fig. S2 B , these cell types were also identified in the ileum, colon, and rectum segments when analyzed separately Fig.

Tuft cell markers POU2F3, GFI1B, and TRPM5 were rarely detected in few cells Fig. S2 C , while the marker DCLK1 was not detected. Classification of the cells revealed distinct cell compositions in the small and large intestine epithelia.

Stem cells and TA cells are highly proliferative cells and responsible for fast renewal of intestinal epithelium. Indeed, the genes related to Wnt signaling or the cell cycle were highly expressed in stem cells and TA cells Fig. S3, A and B; and Table S3.

Notably, stem cells and TA cells are enriched with LGR5 and KI67, respectively. Interestingly, stem cell signature genes of the three segments showed largely different function enrichments Fig.

For example, FABP2 and FABP6, involved in fatty acid metabolic process, were enriched in ileal stem cells, but not in large intestine stem cells, which is consistent with the intestinal functions. By contrast, the signature genes of TA cells in the three segments were highly consistent.

S3 C , like the ones in the mouse intestine Haber et al. Progenitor cells expressed both stem- and proliferation-related genes e. S3, D and E; and Table S4; Clevers and Batlle, , suggesting that they start to gain physiological functions. Furthermore, as shown by the specific genes Fig.

S3 D , progenitor cells exhibited functional difference in different segments. The ones from the ileum were marked by genes related to lipid and protein metabolism, and the ones from the colon and rectum were marked by genes involved in the immune response.

S3 C; also see Fig. We have also observed specific expression of transcription factors in different types of cells CREB3L3, MAF, and NR1H4 in enterocytes; ATOH1, SPEDF, and FOXA3 in goblet cells; SPIB, HES4, and PROX1 in PCs and PLCs; FEV, INSM1, and NEUROD1 in enteroendocrine cells; YBX1 and PHB in both TA and stem cells; HMGB2, FOXM1, and MYBL2 in TA cells; and ASCL2 and ETS2 in stem cells; Fig.

These cell type—dependent transcription factors may play important roles in the differentiation or maintenance of the different cell types. Indeed, INSM1 has been shown to be essential for enteroendocrine cell differentiation Gierl et al. The intestinal tract is the organ for food digestion, nutrient absorption, and processing, such as sugar, lipid, vitamins, and inorganic and organic solutes.

Deficiency in nutrient absorption has been associated with multiple diseases Lin et al. Extensive bowel resection causes defects of nutrient absorption, leading to short bowel syndrome and even death of these patients Tappenden, However, the differential activity of nutrient absorption in different segments of the human intestine is not very clear.

Enterocytes are the major cells responsible for nutrient absorption. To better understand the nutrient-absorption processes in the intestine, we looked into the expression profiles of metabolism-related genes in enterocytes from the ileum, colon, and rectum.

In general, functional enrichment analyses showed that the genes involved in protein digestion and absorption and mineral and organic substance transport were enriched in all three segments. The genes participating in lipid metabolism and drug metabolic process were highly expressed in the ileum, and by contrast, the genes related to small molecule transport were enriched in the large intestine Fig.

As major nutrient transporters, SLC family genes play critical roles in the transport of a wide range of nutrients and metabolites such as glucose, amino acids, vitamins, inorganic solutes, and ions, and their dysfunction has been associated with numerous diseases Lin et al.

We focused on the expression patterns of these transporters in the three intestine segments. In general, the transporter genes involved in lipid, bile salt, vitamin, and water absorption were enriched in the ileum, and the genes related to metal ion and nucleotide absorption were highly expressed in the large intestine Fig.

There were no significantly differences in the expression levels of transporters for amino acid, sugar, and inorganic and organic solutes among these segments.

In addition, although the ketone body metabolism gene ACAT1 was found in the large intestine, most lipid assimilation genes were highly expressed in the small intestine, such as APOA1 and APOM for lecithin, sterol, and stearic acid Fig.

The specific expression of APOA4, APOB, and FABP6 in the ileum was confirmed at the protein level Fig. S4, A—D.

Bile acids, which emulsify fat and fat-soluble nutrients and are essential for their absorption, are secreted into the duodenum through the bile duct Di Ciaula et al.

The genes involved in bile salt reabsorption were mainly found in the ileum, but not large intestine Fig. Similarly, the genes related to vitamin absorption were enriched in the ileum, such as RBP2, TCN2, CYP4F2, and SLC23A1 for the absorption of vitamin A, B 12 , K, and C de Oliveira, ; Goncalves et al.

Notably, the large intestine could also transport vitamin B 12 and A, as suggested by the expression of CD, DHRS9, and RBP4 Arora et al. The expression of aquaporin AQP 1, 3, 7, and 11 was mainly found in the ileum and AQP8 in the large intestine Fig.

Although there was no significant difference in the mean expression of amino acid, sugar, and inorganic and organic solute transporters among the three segments Fig. Consistent with the note that both the small and large intestine are involved in the absorption of essential amino acids, amino acid transporter genes such as SLC3A2, SLC25A39, and SLC25A13 were found in the ileum, colon, and rectum Kobayashi et al.

However, SLC7A7 and SLC7A9, the two genes involved in the transport of neutral or cationic amino acids such as leucine or arginine, were only found in the ileum Suhre et al. SLC38A1, an important cotransporter of glutamine, was confirmed in large intestine Fig. For inorganic solutes, SLC4A7 and SLC34A3 for carbonic acid and phosphoric acid transport, respectively, were mainly expressed in the small intestine, while the gene SLC26A2 for sulfuric acid transport was enriched in the large intestine Heneghan et al.

For organic solutes, the Na-dependent dicarboxylate transporter SLC13A2 was enriched in the small intestine, while the choline transporters SLC44A1 and SLC44A3 were found to be enriched in large intestine Figs.

Both the small and large intestine are involved in sugar absorption, but the small intestine may specially transport monosaccharides such as glucose, fructose, galactose, and xylose based on the enriched expression of SLC5A1, SLC2A5, SLC5A9, and SLC5A11 Coady et al.

The expression of Na, K, and Ca channels KCNS3, ATP2A3, SCNN1A, and SCNN1B was consistent with the idea that the large intestine is important for metal ion absorption Georgiev et al. SCNN1B expression in the large intestine was also confirmed at the protein level Fig.

The Cu transporter SLC31A2 was enriched in the ileum, while the transporters for bivalent metal ions like Zn and Mn SLC39A5, SLC39A8, and SLC39A7 were expressed in both the small and large intestine Bogdan et al. Most importantly, our data also suggested that the large intestine is the major site for nucleotide or nucleotide sugar absorption Fig.

S4 I; Song, Finally, to confirm the functional differences among the three segments, we generated organoids from human ileum, colon, and rectum for various nutrient-uptake experiments.

In the organoids, expression patterns of the genes involved in nutrient absorption were confirmed to be consistent with our single-cell transcriptome data Fig. Next, functional assays revealed that six types of amino acids were highly absorbed in the ileum, consistent with the enriched expression of SLC3A1, SLC7A7, and SLC7A9, which are mainly responsible for the absorption of neutral and cationic amino acids, such as arginine and lysine Suhre et al.

The high expression of SLC44A1 was confirmed in the large intestine, which is consistent with more choline absorption in the organoids derived from the large intestine, while SLC13A2, which is responsible for succinic acid and citric acid absorption, was highly expressed in the small intestine, and the uptake experiments also confirmed this Fig.

SLC2A5 and SLC2A2, which are responsible for galactose, fructose, and mannose absorption, were highly expressed in the small intestine Fig. Consistently, sugar uptake analyses reveled that galactose, fructose, and mannose were mainly absorbed in the small intestine Fig. Differential expression of signaling molecules in enterocytes was also observed in the three segments.

The Wnt signaling mediators FZD5 and DVL3 were also upregulated in the rectum. The high expression of both the proproliferative and prodeath genes suggests that the epithelium of the large intestine, particularly the rectal epithelium, may undergo more rapid turnover.

Although the enteroendocrine cells in the three segments shared a similar expression profile, such as expression of the hormone secretion—related genes PCSK1N and SCG5, some genes showed a clear segment-specific expression pattern Fig.

Analysis of hormone expression in enteroendocrine cells revealed that some of the hormones were highly expressed in the small intestine e. Functional enrichment analysis on the immunity-related genes in the three segments suggested that although both the small and large intestine participate in the antimicrobial humoral response, the small intestine may have a strong defense response to fungi, while the large intestine may be more sensitive to bacterial infection Fig.

Recently, PLCs were reported in the rat ascending colon and human fetal large intestine Gao et al. To further verify the existence of PLCs in the human large intestine, we examined cells in the colon and rectum using Paneth marker genes LYZ, CA4, CA7, and SPIB and found the PLC cluster Fig.

The PLCs in the large intestine and the PCs in the ileum shared a set of highly expressed genes, which include not only genes for microbiotic defense such as LYZ Fig.

Interestingly, PCs in the ileum and PLCs in the large intestine also exhibited marked differences. Functional enrichment of the signature genes showed that PCs and PLCs shared genes involved in lysosome function, neutrophil activation, and Gram-negative bacterium response, while the genes involved in biological oxidation were specific to the ileum and the genes involved in inorganic and sulfur metabolism were enriched in the large intestine Fig.

For example, DEFA5, DEFA6, REG1A, and REG3A were found in ileal PCs, but not in large intestinal PLCs, suggesting that the antimicrobial function may be a major difference between these cells. We found that GNPTAB and SOD3 were specially expressed in PLCs in the human large intestine, but not in PCs in the ileum Fig.

PCs and PLCs shared some common transcription factors involved in Paneth differentiation and viral defense, such as HES1, HES4, and SPIB Fig. However, some other transcription factors exhibited a segment-specific pattern. For instance, SATB2, a chromatin organizer that functions in chromatin remodeling and gene expression and is involved in carcinogenesis, including colorectal cancer Naik and Galande, , was enriched in PLCs of the large intestine.

RELB, which is involved in NF-κB signaling, was highly expressed in the ileal PCs. Interestingly, KIT c-Kit in mouse was detected in some cells, but not in PLCs Fig.

TA cells are derived from stem cells and generate progenitor cells, which eventually differentiate into mature functional cells Gehart and Clevers, However, stem cells, TA cells, and progenitor cells all have proliferation potential, and they are difficult to separate using BrdU or EdU labeling.

Therefore, identification of TA cell—specific markers would be critical for further characterization of these cells. Based on the transcriptome analysis, we found that NUSAP1 nucleolar and spindle associated protein 1 , which is up-regulated in colorectal cancer Han et al.

S5, A and B. Unlike PCNA, NUSAP1 expression did not overlap with LGR5 Figs. In addition, Nusap1 was not colocated with Lgr5 in mouse intestine Fig. Taken together, these observations suggest that NUSAP1 may serve as a potential specific marker of a subset of TA cells. The main function of goblet cells is to secrete mucus that protects the epithelial membrane.

Interestingly, we found that the genes involved in calcium transport were highly expressed in goblet cells of all three segments, while the genes related to the vitamin metabolic process were found in the goblet cells of ileum and the genes related to salmonella infection in the colon Fig. However, unexpectedly, Itln1 was only found in mouse PCs Fig.

S5 G , suggesting a major difference between human and mouse goblet cells. TFF1 encodes a Trefoil factor peptide that plays an important role in response to gastrointestinal mucosa injury and inflammation. As an isoform of TFF1, TFF3 was found in mouse and human goblet cells Aihara et al.

S5, H and I. Moreover, TFF1 protein was found only in the villus of the ileum and in the top zone of crypts of the colon and rectum Fig.

Interestingly, DEFA5 and DEFA6, both of which are expressed in PCs, were enriched in ileal goblet cells Fig. Reg4, which is a marker gene of enteroendocrine cells in the mouse intestine Haber et al. To gain a better understanding of the differences between the human and mouse intestine, we compared our data with the published transcriptome data of the mouse ileum Haber et al.

A total of 6, single cells from human ileum and 3, single cells from mouse ileum were combined and subjected to unsupervised graph-based clustering based on their gene expression profiles. As shown in Fig. This is consistent with the slow cycling of human colon stem cells in the mouse xenograft system for normal human colon organoids Sugimoto et al.

Next, we also examined the conservativeness of the marker genes between human and mouse ilea. In addition to the markers used for cell clustering, such as TMTM37 in enterocyte cells, TFF3 in goblet cells, and CHGB in enteroendocrine cells, many other signature genes were also conserved in both human and mouse, such as FEV and VWA5B2 in enteroendocrine cells and REP15 and BCAS1 in goblet cells Fig.

LYZ, whose homologous genes are Lyz1 and Lyz2 in mouse, is a well-known marker of PCs Sato et al. Interestingly, we also noticed that some genes showed heterogeneities between species in the same cell type. For instance, stem cells from human and mouse ilea shared known markers, such as LGR5, SMOC2, ASCL2, and RGMB Fig.

Furthermore, some genes were enriched in one cell type of human ileum but might exist in another cell type in mouse. For example, TFF3 was expressed in both mouse and human goblet cells, but TFF1 was enriched only in human goblet cells and could not be detected in mouse intestinal cells Figs.

ITLN1, which is expressed in mouse PCs, was enriched in human goblet cells Figs. In summary, these observations further confirm the conservative marker genes in human and mouse intestinal epithelial cells and also reveal special cell type signatures with distinct expression pattern across human and mouse ilea.

As the organ of nutrient digestion and absorption, microbe defense, and endocrine function, the pathophysiological processes and related regulations of the intestine have been extensively studied.

However, many important questions still remain unclear. For example, the functional differences among cells of the same type in different intestine segments are poorly understood. In this study, using single-cell RNA-seq, we surveyed the gene expression profiles of the epithelium in the human ileum, colon, and rectum at single-cell resolution for the first time.

Our data revealed the differential functions of nutrient absorption in these segments. We confirmed the presence of PLCs in the large intestine and found different gene expression patterns between human and mouse. In addition, potential new markers were identified for human TA cells and goblet cells.

These results provide the basis for a better appreciation of human intestine cell constitution and functions as well as further investigation of enterocolitis and intestinal tumorigenesis. Our data unveiled the differential expression of nutrient absorption—related genes in human ileum, colon, and rectum.

High expression of the genes related to transport of lipid, bile salt, vitamin, and water in the ileum indicates that the absorption of these nutrients is mainly accomplished in the small intestine, which is consistent with an earlier report Verkman et al.

Although mean expression of the genes related to the transport of amino acids, sugars, and inorganic and organic solutes was similar among the three segments, the expression of individual transporters varied in different segments, suggesting there may be preferential absorption of different nutrients or metabolites in different parts of the intestine.

Further investigation is needed to obtain a clearer landscape of nutrient absorption in human intestine. PLCs have been recently reported in rat colon and human fetal large intestine Gao et al. Mouse models have been widely used to investigate the mechanisms of human diseases and test drug toxicity and efficacy.

Comprehensive assessment of the differences and similarities between mouse and human is a key for the proper application of mouse models. By comparing the transcriptomes of mouse and human ileum epithelial cells, we found different signature gene expression patterns in mouse and human ileum.

For instance, we found that ITLN1 and Reg4 were enriched in human goblet cells, but not in Paneth and enteroendocrine cells as reported in the mouse ileum Haber et al. Understanding the precise gene expression difference in mouse and human cells would surely help to establish better mouse models for human diseases.

Intestine mucosa were freshly sampled at least 10 cm away from the tumor border in six surgically resected specimens from six patients who had been diagnosed with intestine tumors at Peking University Third Hospital, Beijing, China. All samples were obtained with informed consent, and the study was approved by the Peking University Third Hospital Medical Science Research Ethics Committee M All relevant ethical regulations of Peking University Third Hospital Medical Science Research Ethics Committee were followed.

Intestinal tissues were washed in cold HBSS several times to remove mucus, blood cells and muscle tissue. Connective tissue was scraped away carefully. Then, epithelial tissue was cut into small pieces 5 mm and incubated in 5 mM EDTA in HBSS for 30 min at 4°C.

The pieces were transferred into cold HBSS and vigorously suspended to obtain fractions. Mesenchymal and immune cells were further removed by discarding supernatant after centrifugation 10 s at rpm.

Then, epithelial tissue was enriched through centrifugation 3 min at 1, rpm. After centrifugation 3 min at 1, rpm , the sediment was incubated in Tryple Invitrogen for 20 min at 37°C to obtain single-cell suspension. The libraries were subjected to high-throughput sequencing on an Illumina Hiseq X Ten PE platform, and bp paired-end reads were generated.

The raw sequencing reads were first demultiplexed using Illumina bcl2fastq software to generate bp paired-end read files in FASTQ format. The reads were then aligned to the GRCh38 human reference genome using the Cellranger toolkit version 2.

It's probably fair to say that the single most important process that takes place in the small gut to make such absorption possible is establishment of an electrochemical gradient of sodium across the epithelial cell boundary of the lumen. This is a critical concept and actually quite interesting.

Also, as we will see, understanding this process has undeniably resulted in the saving of millions of lives. To remain viable, all cells are required to maintain a low intracellular concentration of sodium.

Enterocytes in the small intestine absorb large amounts of sodium ion from the lumen, both by cotransport with organic nutrients and by exchange with protons. These pumps export 3 sodium ions from the cell in exchange for 2 potassium ions, thus establishing a gradient of both charge and sodium concentration across the basolateral membrane.

In rats, as a model of all mammals, there are about , sodium pumps per small intestinal enterocyte which collectively allow each cell to transport about 4. Pretty impressive! This flow and accumulation of sodium is ultimately responsible for absorption of water, amino acids and carbohydrates.

Intestinal surface size depends on stem cell division and subsequent amplification of the progenitors in the intestinal crypts, and the effect of PPARα on the intestinal cell division suggests that PPARα is needed for intestinal crypt proliferation.

Therefore, we addressed the role of PPARα in intestinal proliferation using organoid cultures. We isolated crypts from jejuna, and seeded them in matrigel and conditioned medium This suggested that crypt-derived organoids in the culture retain proliferative properties of the source intestines.

Next, we produced organoids from Ppara I-KO and control animals and found reduced budding in the KO organoids Fig. We observed similar results by using a selective pharmacological PPARα antagonist GW, where organoids derived from WT mice developed fewer crypts compared to the vehicle-incubated ones Fig.

To exclude potential PPARα-independent effects of GW, we repeated the experiment in the Ppara I-KO mice and found no differences, suggesting that decreased budding is not due to cytotoxicity or non-specific targets Fig.

Another PPARα antagonist, NXT, produced similar inhibition of crypt budding in WT mice Fig. One-tail Mann—Whitney tests on the histograms refer to the comparison of all organoids between the two groups as in a , and asterisks for difference two-tailed t-test between frequencies of distribution on the histograms.

g Histogram of f. k Histogram of j. n Addition of WNT3A to basal ENR medium EGF, Noggin, R-spondin induces cystic crypts and organoids red asterisks , potentiated by addition of palmitate, scale bar is μm.

To test if the crypt proliferation depends on PPARα-driven fatty acid oxidation, we incubated organoids with etomoxir, an inhibitor of carnitine-palmitoyl transferase 1 CPT1 , necessary for the import of fatty acids into mitochondria for oxidation. We observed a dose-dependent diminishing in the proliferation rates of the crypts isolated from the control mice down to the KO levels.

In contrast, we saw no effect on KO organoids Fig. PPARα antagonism also reduced crypt budding in conditions of increased Ppara expression, both in the cultures from HFD Supplementary Fig. In contrast, PPARα agonism by Wy increased proliferation on HFD Supplementary Fig.

Together, these data show that genetic and pharmacologic inhibition of PPARα reduces crypt proliferation capacity and indicate that fatty acid oxidation metabolically supports this process. To test if this is reflected in the proliferation in vivo, we injected mice with 5-bromodeoxyuracil BrdU.

The reduced villi, but not small intestinal length in the Ppara I-KO mice indicate that PPARα is required for optimal adaptive growth of the crypt-villus axis. We found no difference in the frequency of Paneth, goblet cells or endocrine cells, nor in the most important gut hormones Supplementary Fig.

Transcriptional data from enlarged guts and Ppara I-KO show that the markers of intestinal specification cell types and are mostly not affected at the transcriptional level Supplementary Fig.

A niche for stem cell proliferation is established by WNT proteins, excreted chiefly by Paneth cells, which trigger β-catenin signalling. In our experiments, HFD increased β-catenin levels in whole jejuna, and also in proliferative progenitors Supplementary Fig.

To examine if PPARα may crosstalk with this pathway, we incubated organoids with exogenous WNT3A. Adding WNT3A favours the formation of round cystic organoids rich in stem cells and progenitors, without differentiation into villus-domain cell types By adding palmitate to the culture, WNT3A efficiently promoted stemness in the WT littermates, but the stemness was markedly reduced in organoids from the Ppara I-KO Fig.

To establish the relevance of PPARα-mediated villus growth in humans, and elucidate its role in promoting nutrient absorption, we used commercial human intestinal epithelia biopsies mounted to cell culture insets MatTek EpiIntestinal 3D tissue model, Fig. These tissues obtained from healthy donors maintain crypt-villus polarity native structure and physiology up to several weeks.

We applied small volumes of tissue medium with vehicle or PPARα antagonist GW to the apical side of the epithelium, thus mimicking the interface of the native brush border and the lumen. A five-day incubation with GW moderately reduced the uptake of non-metabolizable dipeptide glycyl-sarcosine GlySar , as measured by its concentration in the basolateral medium Fig.

These effects were not due to any alteration in permeability of the intestinal barrier in the human biopsies, the integrity of which remained intact Fig.

Remarkably, in samples incubated only 8-days with GW the villi shortened Fig. Similar reduction in fatty acid uptake and villi length was obtained with the alternative PPARα antagonist NXT Fig.

a Graphical representation of the human epithelial biopsy culture. l Graphical representation of the mechanism of pharmacological PPARα agonism Wy and antagonism GW , and of the fatty acid oxidation inhibitor etomoxir.

b — h and q are pools from two independent experiments. We next investigated how PPARα regulates fatty acid absorption and villus growth. PPARα regulates fatty acid β-oxidation FAO , as well as aspects of lipid transport and droplet formation 33 , To determine if intestinal FAO is necessary for lipid absorption, we treated human epithelial cultures with etomoxir Fig.

In turn, PPARα activator Wy increased FAO, which was prevented by co-incubation with etomoxir Fig. The activator increased both dipeptide and palmitate uptake Fig. Paradoxically, etomoxir mimicked the effect of the activator.

Co-incubation of Wy with etomoxir not only failed in preventing the increase of the acute palmitate uptake, but further slightly raised it, which was not the case for the dipeptide uptake Fig. This suggests that the decrease of lipid uptake observed in Ppara I-KO and after PPARα antagonism may not be due to decreased FAO Supplementary Fig.

Enterocytes take up dietary fat in form of free fatty acids and monoacylglycerols, which are formed from triglycerides CD36 is a key intestinal fatty acid transporter, while SLC27A4 is the main fatty acid-binding protein that channels the fatty acids through enterocytes and activates them for future metabolism In enterocytes, free fatty acids and monoacylglycerols are re-esterified into triglycerides and exported to the blood in chylomicrons, while a fraction remains in enterocytes as cytosolic LDs especially after a fat-rich meal and in diet-induced obesity.

Formation of cytosolic LDs depends on a number of cytosolic LD-associated proteins, including perilipin-2 and 3 In addition to increasing the expression of Acox1 and Pdk4 , PPARα activation in tissue cultures also enhanced Plin2 Fig.

Etomoxir also increased Plin2 , as noticed earlier On the other hand, peptide and fatty acid transporters Slc15a1 and Slc27a4 showed no or only marginal increase in expression.

Nonetheless, inhibition of PPARα reversed these effects Fig. After one hour, mice were sacrificed and the sections of jejuna were treated with neutral lipid stains LipidTOX or Oil Red O Fig.

Quantification of lipid droplets in the intestinal epithelium revealed that the enterocytes of Ppara I-KO mice had diminished cytoplasmic lipid content, compared to epithelium of the control littermates Fig.

The lipid droplets of the Ppara I-KO mice were smaller than those of the controls Fig. In Ppara I-KO jejuna, Cd36 , Slc27a2 and Slc27a4 expression was decreased, whereas genes critical for glucose and peptide absorption, the re-esterification of absorbed fatty acids, packaging in chylomicrons, and mitochondrial content were not affected Fig.

In contrast, Plin2 expression was strongly suppressed in Ppara I-KO, both at mRNA and protein level Fig. PLIN2 also known as adipophilin, ADRP is critical for LD formation and stability, and its absence hampers the ability to form lipid droplets in many tissues 46 , 47 , Therefore, we further investigated the PPARα-dependant response of PLIN2 to palmitate load in intestinal organoids from Ppara I-KO and control mice.

Palmitate increased PLIN2 protein levels over 8-fold in WT organoids. Conversely, palmitate enhanced the Plin2 transcript for over 4-fold in WT organoids, while PPARα agonism led to over fold increase of the Plin2 levels.

Both palmitate and PPARα agonism had no effect on Plin2 expression in Ppara I-KO organoids Fig. Collectively, these findings suggest that lack of PPARα delays fat absorption through the intestine and that, at least partially, this is mediated by downregulation of perilipin 2, necessary for enterocyte lipid droplet formation.

Our study addresses a fundamental question on the metabolic triggers and mechanisms regulating the plasticity and function of the intestinal lining.

The work shows that the intestinal functional and morphological alterations depend on the food amount. Using multiple genetic models, and systematic in vivo approaches, we demonstrate that while several energetic pathways are dispensable, the intestinal PPARα-mediated lipid metabolism is of key importance for the adaptive villi lengthening and increased absorptive function in mice and human intestinal biopsies.

This work proposes a concept in which the intestinal plasticity allows optimisation of caloric uptake from the consumed food, by coupling energetically costly intestinal epithelial maintenance to food availability.

Gut reshaping involves elongation, villus growth, microvilli extension, and upregulation of uptake transporters, though not all of them need to be employed equally and at the same time. These processes require energy resources.

While our data show that gut expansion mobilizes glycolysis, gluconeogenesis and glutamate utilization pathways; there is a robust capacity for compensation in case one of them is affected. However, we found that PPARα is indispensable for adaptive villi growth and increased lipid transport.

While fatty acid oxidation that is orchestrated by PPARα was needed for crypt-villus growth, its inhibition was insufficient to prevent intestinal lipid transport. Instead, our data suggest an alternative pathway, where the intestinal lipid droplet formation is reduced following PPARα depletion, coupled to a marked reduction of PLIN2, a key mediator of lipid droplet formation and growth In DIO, PLIN2 is upregulated, forming ring-like structures around cytosolic lipid droplets as they grow 44 , 49 , and Plin2 deletion affects lipid absorption in intestines and ameliorates DIO In our experiments, PPARα deletion induced complete blunting of the Plin2 expression, and fully prevented its elevation driven by an increase in the fatty acid palmitate, which seemed sufficient to suppress the total TG absorption in line with data from the global Plin2 -KO mice This notion can be further supported by the current understanding of cytosolic lipid droplets representing a transitional pool of lipids that optimizes absorption during food consumption Therefore, the reduced lipid uptake following PPARα inhibition may be a result of three complementary effects: decreased intestinal surface due to shorter villi, downregulation of fatty acid transporters on the apical surface of brush border, and reduced expression of Plin2 in the enterocytes.

All three layers of regulation were considerably lower with inhibition or knock-out of Ppara , explaining the potent reduction of lipid uptake. These mechanisms also affect sugar and peptide transport, though ex vivo uptake assays and the respective transporter expression data suggest that their uptake is attenuated to a lesser extent than fatty acids.

We found no effect of PPARα deletion on the intestinal lipoprotein assembly machinery, but rather a decrease of fatty acid uptake, packaging and export, independent of fatty acid oxidation status.

Earlier reports suggested that docosahexaenoic acid 51 and benzafibrate 52 , 53 , activators of PPARα and fatty acid oxidation, attenuate postprandial hyperlipidaemia in vivo and lower basal TG secretion in Caco-2 enterocyte cultures. It is important to note that these studies used exclusively pharmacological approaches, did not measure TG build-up and export in enterocytes after fat load, nor investigated for morphological changes on enterocytes, or contributions from other organs where the pharmacological PPARα activation would play a role.

In line with our findings, it is known that ISCs are sensitive to dietary clues, and fatty acids provided by HFD increase ISC proliferation. This was recently attributed to activation of PPARδ 16 , an abundant PPAR isoform in the crypt region, and to PRDM16, a transcriptional regulator of FAO However, deletion of PPARδ did not alter villi or gut length Moreover, we found no or very small increase in its expression in any of the enlarged intestines, compared to the PPARα.

As PPARδ is more dominant isoform in duodenum, and PPARα in jejunum Supplementary Fig. However, in contrast to Ppara , the Ppard I-KO triggers increased fat gain during HFD 55 , indicating that the mechanism of fat handling is distinct in the two knockouts. The contribution of PPARα in the intestinal response to HFD was not addressed in these studies, but Hmgcs2 is a well-known target of PPARα 33 , 41 , while PRDM16 is the upstream regulator of PPARα and other genes of FAO, especially the upper intestine.

Fat-rich ketogenic diet activates HMGCS2 the rate-limiting enzyme of ketogenesis in ISC, which stimulates Notch signalling to promote ISC self-renewal In line with this, our data suggest PPARα as an indispensable mediator of intestinal homeostasis and cell division in jejunum, likely downstream of PRDM It is important to note that various genetic and dietary models can have pleiotropic effects, which may contribute to the correlations observed between food intake and gut surface area.

While our study points to the critical contribution of the food amount, it does not exclude that certain food components 29 can affect the intestinal surface and function independently, or in concert with the food amount.

Moreover, the transcription programs orchestrated by PPARα are indispensable for the villi growth in presence of dietary lipids, however, the direct link between the lipid metabolism and the food amount pends further investigations.

As recently reported, PPAR and RXR signalling is involved in the complex transitions between early regeneration and latter differentiation in intestinal organoids 57 , and knock-down of RXR, a PPAR co-factor, reduced enterocyte generation, but increased the regenerative capacity.

Intriguingly, while PPARα coordinates lipid metabolism and is upregulated by lipid-rich diets, there is no direct correlation between amount of ingested lipid and intestinal surface. Indeed, palmitate and HFD increase crypt formation and stem cell division without resulting in expansion of the absorptive surface our data and All this shows that PPARα is essential, but not sufficient for gut surface increase, and that additional mechanisms are necessary to release the break on the intestinal surface expansion.

In the case of overeating, this might involve activation of other energy pathways in concert with PPARα, and sensing of mechanical pressure in the intestines. Mucosa thickening is a hallmark of intestinal adaptations that follow intestinal resection.

It is, at the molecular level, a poorly understood process that includes bowel lengthening, growth of villi, and induction of transporter expression The PPARα-driven mechanism of villus growth could explain why fatty acids such as palmitate or linoleate are the most effective dietary therapy that promotes mucosa re-growth after bowel resection 59 , 60 , a process that can be further potentiated by feeding prostaglandins Fatty acids and eicosanoids are strong inducers of PPARα.

Conversely, disruption of PPARα and fatty acid oxidation is found in celiac disease, a condition characterized by shortened villi and malabsorption Hepatic steatosis and increased adiposity are major risk factors for the development of metabolic syndrome.

PPARα ablation in the liver and adipose tissue facilitates fat accumulation in these tissues by reducing levels of fatty acid oxidation Unexpectedly, Ppara deletion in the intestine lowers fat uptake in the liver and fat. Intestinal lipid droplet formation and trafficking regulated by PPARα, therefore, represent important rate-limiting steps in systemic lipid metabolism.

Inhibition of this process moderates the excursions of plasma triglycerides after a lipid-rich meal. If pharmacological inhibition of PPARα or lipid droplet formation could be limited to intestines, this would serve as an option for reducing fat absorption and hyperlipidaemia, but also total caloric uptake.

As a whole, the remarkable gut plasticity that permits gut and villi to be shrunk or enlarged is, therefore, an asset as a reversible alternative to gastric bypass surgery, or other interventions that aim at reducing body weight gain and obesity-related complications.

Genotyping protocols and primers for Hk2, Pck1 and Glud1 mice were taken from respective suppliers. They were all crossed with villin-CreERT2 mice B6. Mice crossed with villin-CreERT2 line were administered in total 3 intraperitoneal i.

Efficiency of knock-out was confirmed by PCR in whole intestinal tissues and in the sorted intestinal crypt cells. Deletion and tissue specificity were checked as previously characterized Lgr5-EGFP-IRES-creERT2 mice were purchased from Jackson Laboratory.

All mice were bred, housed and experimented with in SPF facilities, except Ppara mice, which were bred and experimented with in the conventional zone. Cold-exposed mice were always kept two per cage, without cotton pads and houses, separated by the genotype, while HFD and HF-HS mice were kept 2—4 mice per cage, with the enrichment, separated by the genotype the cohorts for the food intake and faeces measurements , or mixed in the repeated experiments.

All mice were males, unless specified otherwise in a Figure legend, and in vivo measurements were not blinded. Animal research was conducted according to the Swiss regulations Federal Animal Welfare Act and guidelines RESAL - Lemanic Animal Facility Network.

The different foods are summarised in Supplementary Table 2. HFD no fiber diet in Supplementary Figure 1d, h, i , and Fig. Additionally, chow diets from SAFE diets SAFE and sniff V were used in Supplementary Fig.

All foods were γ-irradiated. Male 14 to week-old Ppara mice were placed in the calorimetric cages Labmaster, TSE, BadHomburg, Germany to measure food intake, locomotor activity, oxygen consumption and CO 2 production during seven days; energy expenditure was normalized to lean mass.

Blood samples during oral and intraperitoneal glucose tolerance tests OGTT, IPGTT and acute fat load test were collected from the tail vein in EDTA coated tubes Sarstedt, CB K2E. For bomb calorimetry of the faeces, hour faeces were collected from the cage bedding 2 mice per cage , vacuum dried, pulverized to the fine powder and analysed in the calorimeter Parr, , USA.

Blood collection. GLP-1, GIP, glucagon and ghrelin were measured by Bio-Plex Pro Mouse Diabetes panel , from plasma diluted according to instructions, on Bio-Plex Luminex platform Biorad. Intestines were carefully unfolded and samples taken ensuring that they are from the same sites between different mice.

RNA isolation and qPCR. RNA from tissues and cell cultures was isolated with TRIzol Life Technologies , cDNA synthetized by High-Capacity cDNA Reverse Transcription Kit Applied Biosciences.

Transcript levels were measured by quantitative RT-PCR using SYBR Green, on the instrument LightCycler Roche , and the levels were normalized to Tbp or Rplp0 , as indicated in the legend, or to epithelial marker Epcam for the organoid cultures.

The primers used for the qPCR are provided in the Supplementary Table 1. Metabolomics analysis was done as described earlier 3 , Complete metabolomics measurements and statistical methods are provided in the Supplementary Data 1 of this paper.

RNA Sequencing. RNA was isolated by TRIzol regent. Three samples were submitted per group; each being a pool of two equal amounts of RNA isolated from proximal jejunum. The reads were mapped with the TopHat v. Biological quality control and summarization were done with RSeQC Briefly, the counts were normalized according to the library size and filtered.

The genes having a count above 1 count per million reads cpm in at least 3 samples were kept for the analysis. The differentially expressed genes tests were done with a GLM general linear model with a negative binomial distribution.

Normalized counts are shown. For comparison on the graphs in Fig. Western blot. Western blots were probed with antibodies against: PLIN2 guinea pig, , MyBioSource , γ-tubulin , Sigma Aldrich T , GAPDH , abcam , PCNA , origene, TA , PEPCK , sc, Santa Cruz , GDH , Cell Signalling.

Quantification was done from Oil Red O staining, in FIJI ImageJ software 1. Villi analysis. Z1 platform Zeiss with 20x objective.

Perimeters were traced around complete sections, following outer edge of submucosa. Villi lengths were measured in ZEN 2 software by tracing intact, full-length villi from the beginning of the villus domain until the top. Broken, cross-cut, or degraded villi were not measured.

In total, 5—10 villi per section from 2—3 sections per jejunum were measured, and the average length reported. Microvilli were imaged in the samples from the proximal jejuna by the transmission electron microscope Morgagni FEI Company, Eindhoven, Netherlands at EM Core Facility of University of Geneva.

Antibodies : LysC sc, Santa Cruz , anti-BrdU ab, Abcam , chromogranin A sc, Santa Cruz , Alcian blue was used as previously described 3. For histological experiments, researchers were blinded to group allocation during processing and quantification of the sample through labelling of samples by the numeric codes.

Intestinal crypts were isolated and the cultured as described before For WENR medium, murine WNT3A Peprotech was added to ENR in the concentration indicated. Crypts were harvested for RNA or protein isolation on days 7—10 by dissolving matrigel in ice-cold PBS.

Crypts from Lgr5-GFP mice were isolated as above, and suspension of villi in PBS was obtained by gently scraping longitudinally opened section of proximal-to-mid jejunum by microscope cover glass.

The cells were sorted on BD FACS ARIA Fusion, with software BD FACS Diva Software version 8. FACS plots have been produced by FlowJoTM version Cells were sorted in RTL solution Qiagen. MatTek obtained tissue samples from accredited institutions after informed consent of the donor or next of kin for use of cells or tissues for research purposes.

Biopsy cultures were maintained in proprietary medium supplanted on day 2 on apical side with the inhibitors in the concentrations described in the previous section, and renewed every day. Free fatty acids in sampled aliquots were measured by NEFA-HR kit Wako.

Membranes with the tissues were excised from the insets, cut in half and saved for RNA isolation and histology. Statistical tests are specified in the figure legends. To calculate significances, we used: for normally distributed continuous data e.

body weight, plasma triglycerides, qPCR etc. For the multiple comparisons, we used non-paired one-way ANOVA, with Dunnet post-hoc correction, the alpha 0. For the gene expression levels by RNA sequencing, significances are calculated by general linear model with negative binomial distribution; P values without correction are shown in the figures.

Graphs and statistical analysis were done in GraphPad Prism 8. Further information on research design is available in the Nature Research Reporting Summary linked to this article.

Sequencing data associated with this study have been deposited to the Gene Expression Omnibus with accession codes GSE , GSE , and GSE Source data are provided with this paper. Metabolomic source data are provided in the Supplementary Data 1 of the paper.

All other data used in this study are available from the corresponding author upon reasonable request. Speakman, J. Fat: an evolving issue. Model Mech. Article CAS PubMed PubMed Central Google Scholar.

Human genetics illuminates the paths to metabolic disease. Nature , — Article ADS PubMed Google Scholar. Chevalier, C. et al. Gut microbiota orchestrates energy homeostasis during cold. Cell , — Article CAS PubMed Google Scholar. Dalby, M. Dietary uncoupling of gut microbiota and energy harvesting from obesity and glucose tolerance in mice.

Cell Rep. Dailey, M. Nutrient-induced intestinal adaption and its effect in obesity. Toloza, E. Nutrient extraction by cold-exposed mice: a test of digestive safety margins. CAS PubMed Google Scholar. Guzman, I. Small bowel length in hyperlipidemia and massive obesity.

Hosseinpour, M. Evaluation of small bowel measurement in alive patients. Article Google Scholar. Purandare, A. Variability of length of small intestine in indian population and its correlation with type 2 diabetes mellitus and obesity.

Article PubMed Google Scholar. Bekheit, M. Correlation between the total small bowel length and anthropometric measures in living humans: Cross-Sectional Study.

Rubino, F. Metabolic surgery: the role of the gastrointestinal tract in diabetes mellitus. Article PubMed PubMed Central Google Scholar. Barker, N. Identification of stem cells in small intestine and colon by marker gene Lgr5.

Nature , —U Article ADS CAS PubMed Google Scholar. Adult intestinal stem cells: critical drivers of epithelial homeostasis and regeneration. Cell Biol. Yilmaz, O. mTORC1 in the Paneth cell niche couples intestinal stem-cell function to calorie intake.

Article ADS CAS PubMed PubMed Central Google Scholar. Mao, J. Overnutrition stimulates intestinal epithelium proliferation through beta-catenin signaling in obese mice. Diabetes 62 , — Beyaz, S. High-fat diet enhances stemness and tumorigenicity of intestinal progenitors.

Nature , 53—58 Goncalves, M. High-fructose corn syrup enhances intestinal tumor growth in mice. Science , — Rodriguez-Colman, M. Interplay between metabolic identities in the intestinal crypt supports stem cell function. Nature , Mihaylova, M. Fasting activates fatty acid oxidation to enhance intestinal stem cell function during homeostasis and aging.

Cell Stem Cell 22 , — e Burrin, D. Metabolic fate and function of dietary glutamate in the gut. Reeds, P. Intestinal glutamate metabolism. Turnbaugh, P. An obesity-associated gut microbiome with increased capacity for energy harvest. Soty, M. Gut-brain glucose signaling in energy homeostasis. Cell Metab.

Saeidi, N. Reprogramming of intestinal glucose metabolism and glycemic control in rats after gastric bypass. Troy, S. Intestinal gluconeogenesis is a key factor for early metabolic changes after gastric bypass but not after gastric lap-band in mice. Montagner, A.

Liver PPAR alpha is crucial for whole-body fatty acid homeostasis and is protective against NAFLD. Gut 65 , — Costet, P. Peroxisome proliferator-activated receptor alpha-isoform deficiency leads to progressive dyslipidemia with sexually dimorphic obesity and steatosis.

Coleman, D. A historical perspective on leptin. Med 16 , — Taylor, S. Dietary fructose improves intestinal cell survival and nutrient absorption. Powell, W.

Biosynthesis, biological effects, and receptors of hydroxyeicosatetraenoic acids HETEs and oxoeicosatetraenoic acids oxo-ETEs derived from arachidonic acid.

Biochim Biophys. Acta , — Xu, H. Molecular recognition of fatty acids by peroxisome proliferator-activated receptors. Cell 3 , — Caillon, A. The OEA effect on food intake is independent from the presence of PPAR alpha in the intestine and the nodose ganglion, while the impact of OEA on energy expenditure requires the presence of PPAR alpha in mice.

Metabolism 87 , 13—17 Dubois, V. Distinct but complementary contributions of PPAR isotypes to energy homeostasis. Invest , — Hirai, T. Karimian Azari, E. Possible role of intestinal fatty acid oxidation in the eating-inhibitory effect of the PPAR-alpha agonist Wy in high-fat diet fed rats.

PLoS One 8 , e Article ADS PubMed PubMed Central Google Scholar. Bunger, M. Genome-wide analysis of PPARalpha activation in murine small intestine. Genomics 30 , — Fu, J. Oleylethanolamide regulates feeding and body weight through activation of the nuclear receptor PPAR-alpha.

Nature , 90—93 Colin, S. Activation of intestinal peroxisome proliferator-activated receptor-alpha increases high-density lipoprotein production. Heart J. Sato, T. Paneth cells constitute the niche for Lgr5 stem cells in intestinal crypts.

Ayehunie, S. Human Primary Cell-Based Organotypic Microtissues for Modeling Small Intestinal Drug Absorption. Res 35 , 72 Rakhshandehroo, M. Peroxisome proliferator-activated receptor alpha target genes. Beilstein, F. Characteristics and functions of lipid droplets and associated proteins in enterocytes.

Cell Res , — Mashek, D. Long-chain acyl-CoA synthetases and fatty acid channeling. Future Lipido. Article CAS Google Scholar. Diet induced obesity alters intestinal cytoplasmic lipid droplet morphology and proteome in the postprandial response to dietary fat.

Palmitate increased PLIN2 protein levels over 8-fold in WT organoids. Conversely, palmitate enhanced the Plin2 transcript for over 4-fold in WT organoids, while PPARα agonism led to over fold increase of the Plin2 levels. Both palmitate and PPARα agonism had no effect on Plin2 expression in Ppara I-KO organoids Fig.

Collectively, these findings suggest that lack of PPARα delays fat absorption through the intestine and that, at least partially, this is mediated by downregulation of perilipin 2, necessary for enterocyte lipid droplet formation. Our study addresses a fundamental question on the metabolic triggers and mechanisms regulating the plasticity and function of the intestinal lining.

The work shows that the intestinal functional and morphological alterations depend on the food amount. Using multiple genetic models, and systematic in vivo approaches, we demonstrate that while several energetic pathways are dispensable, the intestinal PPARα-mediated lipid metabolism is of key importance for the adaptive villi lengthening and increased absorptive function in mice and human intestinal biopsies.

This work proposes a concept in which the intestinal plasticity allows optimisation of caloric uptake from the consumed food, by coupling energetically costly intestinal epithelial maintenance to food availability. Gut reshaping involves elongation, villus growth, microvilli extension, and upregulation of uptake transporters, though not all of them need to be employed equally and at the same time.

These processes require energy resources. While our data show that gut expansion mobilizes glycolysis, gluconeogenesis and glutamate utilization pathways; there is a robust capacity for compensation in case one of them is affected.

However, we found that PPARα is indispensable for adaptive villi growth and increased lipid transport. While fatty acid oxidation that is orchestrated by PPARα was needed for crypt-villus growth, its inhibition was insufficient to prevent intestinal lipid transport.

Instead, our data suggest an alternative pathway, where the intestinal lipid droplet formation is reduced following PPARα depletion, coupled to a marked reduction of PLIN2, a key mediator of lipid droplet formation and growth In DIO, PLIN2 is upregulated, forming ring-like structures around cytosolic lipid droplets as they grow 44 , 49 , and Plin2 deletion affects lipid absorption in intestines and ameliorates DIO In our experiments, PPARα deletion induced complete blunting of the Plin2 expression, and fully prevented its elevation driven by an increase in the fatty acid palmitate, which seemed sufficient to suppress the total TG absorption in line with data from the global Plin2 -KO mice This notion can be further supported by the current understanding of cytosolic lipid droplets representing a transitional pool of lipids that optimizes absorption during food consumption Therefore, the reduced lipid uptake following PPARα inhibition may be a result of three complementary effects: decreased intestinal surface due to shorter villi, downregulation of fatty acid transporters on the apical surface of brush border, and reduced expression of Plin2 in the enterocytes.

All three layers of regulation were considerably lower with inhibition or knock-out of Ppara , explaining the potent reduction of lipid uptake.

These mechanisms also affect sugar and peptide transport, though ex vivo uptake assays and the respective transporter expression data suggest that their uptake is attenuated to a lesser extent than fatty acids. We found no effect of PPARα deletion on the intestinal lipoprotein assembly machinery, but rather a decrease of fatty acid uptake, packaging and export, independent of fatty acid oxidation status.

Earlier reports suggested that docosahexaenoic acid 51 and benzafibrate 52 , 53 , activators of PPARα and fatty acid oxidation, attenuate postprandial hyperlipidaemia in vivo and lower basal TG secretion in Caco-2 enterocyte cultures. It is important to note that these studies used exclusively pharmacological approaches, did not measure TG build-up and export in enterocytes after fat load, nor investigated for morphological changes on enterocytes, or contributions from other organs where the pharmacological PPARα activation would play a role.

In line with our findings, it is known that ISCs are sensitive to dietary clues, and fatty acids provided by HFD increase ISC proliferation. This was recently attributed to activation of PPARδ 16 , an abundant PPAR isoform in the crypt region, and to PRDM16, a transcriptional regulator of FAO However, deletion of PPARδ did not alter villi or gut length Moreover, we found no or very small increase in its expression in any of the enlarged intestines, compared to the PPARα.

As PPARδ is more dominant isoform in duodenum, and PPARα in jejunum Supplementary Fig. However, in contrast to Ppara , the Ppard I-KO triggers increased fat gain during HFD 55 , indicating that the mechanism of fat handling is distinct in the two knockouts.

The contribution of PPARα in the intestinal response to HFD was not addressed in these studies, but Hmgcs2 is a well-known target of PPARα 33 , 41 , while PRDM16 is the upstream regulator of PPARα and other genes of FAO, especially the upper intestine. Fat-rich ketogenic diet activates HMGCS2 the rate-limiting enzyme of ketogenesis in ISC, which stimulates Notch signalling to promote ISC self-renewal In line with this, our data suggest PPARα as an indispensable mediator of intestinal homeostasis and cell division in jejunum, likely downstream of PRDM It is important to note that various genetic and dietary models can have pleiotropic effects, which may contribute to the correlations observed between food intake and gut surface area.

While our study points to the critical contribution of the food amount, it does not exclude that certain food components 29 can affect the intestinal surface and function independently, or in concert with the food amount.

Moreover, the transcription programs orchestrated by PPARα are indispensable for the villi growth in presence of dietary lipids, however, the direct link between the lipid metabolism and the food amount pends further investigations. As recently reported, PPAR and RXR signalling is involved in the complex transitions between early regeneration and latter differentiation in intestinal organoids 57 , and knock-down of RXR, a PPAR co-factor, reduced enterocyte generation, but increased the regenerative capacity.

Intriguingly, while PPARα coordinates lipid metabolism and is upregulated by lipid-rich diets, there is no direct correlation between amount of ingested lipid and intestinal surface.

Indeed, palmitate and HFD increase crypt formation and stem cell division without resulting in expansion of the absorptive surface our data and All this shows that PPARα is essential, but not sufficient for gut surface increase, and that additional mechanisms are necessary to release the break on the intestinal surface expansion.

In the case of overeating, this might involve activation of other energy pathways in concert with PPARα, and sensing of mechanical pressure in the intestines. Mucosa thickening is a hallmark of intestinal adaptations that follow intestinal resection. It is, at the molecular level, a poorly understood process that includes bowel lengthening, growth of villi, and induction of transporter expression The PPARα-driven mechanism of villus growth could explain why fatty acids such as palmitate or linoleate are the most effective dietary therapy that promotes mucosa re-growth after bowel resection 59 , 60 , a process that can be further potentiated by feeding prostaglandins Fatty acids and eicosanoids are strong inducers of PPARα.

Conversely, disruption of PPARα and fatty acid oxidation is found in celiac disease, a condition characterized by shortened villi and malabsorption Hepatic steatosis and increased adiposity are major risk factors for the development of metabolic syndrome.

PPARα ablation in the liver and adipose tissue facilitates fat accumulation in these tissues by reducing levels of fatty acid oxidation Unexpectedly, Ppara deletion in the intestine lowers fat uptake in the liver and fat.

Intestinal lipid droplet formation and trafficking regulated by PPARα, therefore, represent important rate-limiting steps in systemic lipid metabolism. Inhibition of this process moderates the excursions of plasma triglycerides after a lipid-rich meal. If pharmacological inhibition of PPARα or lipid droplet formation could be limited to intestines, this would serve as an option for reducing fat absorption and hyperlipidaemia, but also total caloric uptake.

As a whole, the remarkable gut plasticity that permits gut and villi to be shrunk or enlarged is, therefore, an asset as a reversible alternative to gastric bypass surgery, or other interventions that aim at reducing body weight gain and obesity-related complications.

Genotyping protocols and primers for Hk2, Pck1 and Glud1 mice were taken from respective suppliers. They were all crossed with villin-CreERT2 mice B6. Mice crossed with villin-CreERT2 line were administered in total 3 intraperitoneal i. Efficiency of knock-out was confirmed by PCR in whole intestinal tissues and in the sorted intestinal crypt cells.

Deletion and tissue specificity were checked as previously characterized Lgr5-EGFP-IRES-creERT2 mice were purchased from Jackson Laboratory.

All mice were bred, housed and experimented with in SPF facilities, except Ppara mice, which were bred and experimented with in the conventional zone. Cold-exposed mice were always kept two per cage, without cotton pads and houses, separated by the genotype, while HFD and HF-HS mice were kept 2—4 mice per cage, with the enrichment, separated by the genotype the cohorts for the food intake and faeces measurements , or mixed in the repeated experiments.

All mice were males, unless specified otherwise in a Figure legend, and in vivo measurements were not blinded. Animal research was conducted according to the Swiss regulations Federal Animal Welfare Act and guidelines RESAL - Lemanic Animal Facility Network.

The different foods are summarised in Supplementary Table 2. HFD no fiber diet in Supplementary Figure 1d, h, i , and Fig.

Additionally, chow diets from SAFE diets SAFE and sniff V were used in Supplementary Fig. All foods were γ-irradiated. Male 14 to week-old Ppara mice were placed in the calorimetric cages Labmaster, TSE, BadHomburg, Germany to measure food intake, locomotor activity, oxygen consumption and CO 2 production during seven days; energy expenditure was normalized to lean mass.

Blood samples during oral and intraperitoneal glucose tolerance tests OGTT, IPGTT and acute fat load test were collected from the tail vein in EDTA coated tubes Sarstedt, CB K2E.

For bomb calorimetry of the faeces, hour faeces were collected from the cage bedding 2 mice per cage , vacuum dried, pulverized to the fine powder and analysed in the calorimeter Parr, , USA.

Blood collection. GLP-1, GIP, glucagon and ghrelin were measured by Bio-Plex Pro Mouse Diabetes panel , from plasma diluted according to instructions, on Bio-Plex Luminex platform Biorad.

Intestines were carefully unfolded and samples taken ensuring that they are from the same sites between different mice. RNA isolation and qPCR. RNA from tissues and cell cultures was isolated with TRIzol Life Technologies , cDNA synthetized by High-Capacity cDNA Reverse Transcription Kit Applied Biosciences.

Transcript levels were measured by quantitative RT-PCR using SYBR Green, on the instrument LightCycler Roche , and the levels were normalized to Tbp or Rplp0 , as indicated in the legend, or to epithelial marker Epcam for the organoid cultures.

The primers used for the qPCR are provided in the Supplementary Table 1. Metabolomics analysis was done as described earlier 3 , Complete metabolomics measurements and statistical methods are provided in the Supplementary Data 1 of this paper.

RNA Sequencing. RNA was isolated by TRIzol regent. Three samples were submitted per group; each being a pool of two equal amounts of RNA isolated from proximal jejunum. The reads were mapped with the TopHat v. Biological quality control and summarization were done with RSeQC Briefly, the counts were normalized according to the library size and filtered.

The genes having a count above 1 count per million reads cpm in at least 3 samples were kept for the analysis. The differentially expressed genes tests were done with a GLM general linear model with a negative binomial distribution.

Normalized counts are shown. For comparison on the graphs in Fig. Western blot. Western blots were probed with antibodies against: PLIN2 guinea pig, , MyBioSource , γ-tubulin , Sigma Aldrich T , GAPDH , abcam , PCNA , origene, TA , PEPCK , sc, Santa Cruz , GDH , Cell Signalling.

Quantification was done from Oil Red O staining, in FIJI ImageJ software 1. Villi analysis. Z1 platform Zeiss with 20x objective. Perimeters were traced around complete sections, following outer edge of submucosa. Villi lengths were measured in ZEN 2 software by tracing intact, full-length villi from the beginning of the villus domain until the top.

Broken, cross-cut, or degraded villi were not measured. In total, 5—10 villi per section from 2—3 sections per jejunum were measured, and the average length reported. Microvilli were imaged in the samples from the proximal jejuna by the transmission electron microscope Morgagni FEI Company, Eindhoven, Netherlands at EM Core Facility of University of Geneva.

Antibodies : LysC sc, Santa Cruz , anti-BrdU ab, Abcam , chromogranin A sc, Santa Cruz , Alcian blue was used as previously described 3. For histological experiments, researchers were blinded to group allocation during processing and quantification of the sample through labelling of samples by the numeric codes.

Intestinal crypts were isolated and the cultured as described before For WENR medium, murine WNT3A Peprotech was added to ENR in the concentration indicated. Crypts were harvested for RNA or protein isolation on days 7—10 by dissolving matrigel in ice-cold PBS.

Crypts from Lgr5-GFP mice were isolated as above, and suspension of villi in PBS was obtained by gently scraping longitudinally opened section of proximal-to-mid jejunum by microscope cover glass. The cells were sorted on BD FACS ARIA Fusion, with software BD FACS Diva Software version 8.

FACS plots have been produced by FlowJoTM version Cells were sorted in RTL solution Qiagen. MatTek obtained tissue samples from accredited institutions after informed consent of the donor or next of kin for use of cells or tissues for research purposes.

Biopsy cultures were maintained in proprietary medium supplanted on day 2 on apical side with the inhibitors in the concentrations described in the previous section, and renewed every day. Free fatty acids in sampled aliquots were measured by NEFA-HR kit Wako. Membranes with the tissues were excised from the insets, cut in half and saved for RNA isolation and histology.

Statistical tests are specified in the figure legends. To calculate significances, we used: for normally distributed continuous data e. body weight, plasma triglycerides, qPCR etc.

For the multiple comparisons, we used non-paired one-way ANOVA, with Dunnet post-hoc correction, the alpha 0. For the gene expression levels by RNA sequencing, significances are calculated by general linear model with negative binomial distribution; P values without correction are shown in the figures.

Graphs and statistical analysis were done in GraphPad Prism 8. Further information on research design is available in the Nature Research Reporting Summary linked to this article. Sequencing data associated with this study have been deposited to the Gene Expression Omnibus with accession codes GSE , GSE , and GSE Source data are provided with this paper.

Metabolomic source data are provided in the Supplementary Data 1 of the paper. All other data used in this study are available from the corresponding author upon reasonable request. Speakman, J. Fat: an evolving issue. Model Mech. Article CAS PubMed PubMed Central Google Scholar.

Human genetics illuminates the paths to metabolic disease. Nature , — Article ADS PubMed Google Scholar. Chevalier, C. et al. Gut microbiota orchestrates energy homeostasis during cold.

Cell , — Article CAS PubMed Google Scholar. Dalby, M. Dietary uncoupling of gut microbiota and energy harvesting from obesity and glucose tolerance in mice.

Cell Rep. Dailey, M. Nutrient-induced intestinal adaption and its effect in obesity. Toloza, E. Nutrient extraction by cold-exposed mice: a test of digestive safety margins. CAS PubMed Google Scholar. Guzman, I. Small bowel length in hyperlipidemia and massive obesity.

Hosseinpour, M. Evaluation of small bowel measurement in alive patients. Article Google Scholar. Purandare, A. Variability of length of small intestine in indian population and its correlation with type 2 diabetes mellitus and obesity. Article PubMed Google Scholar.

Bekheit, M. Correlation between the total small bowel length and anthropometric measures in living humans: Cross-Sectional Study. Rubino, F. Metabolic surgery: the role of the gastrointestinal tract in diabetes mellitus.

Article PubMed PubMed Central Google Scholar. Barker, N. Identification of stem cells in small intestine and colon by marker gene Lgr5. Nature , —U Article ADS CAS PubMed Google Scholar. Adult intestinal stem cells: critical drivers of epithelial homeostasis and regeneration.

Cell Biol. Yilmaz, O. mTORC1 in the Paneth cell niche couples intestinal stem-cell function to calorie intake.

Article ADS CAS PubMed PubMed Central Google Scholar. Mao, J. Overnutrition stimulates intestinal epithelium proliferation through beta-catenin signaling in obese mice.

Diabetes 62 , — Beyaz, S. High-fat diet enhances stemness and tumorigenicity of intestinal progenitors. Nature , 53—58 Goncalves, M.

High-fructose corn syrup enhances intestinal tumor growth in mice. Science , — Rodriguez-Colman, M. Interplay between metabolic identities in the intestinal crypt supports stem cell function.

Nature , Mihaylova, M. Fasting activates fatty acid oxidation to enhance intestinal stem cell function during homeostasis and aging. Cell Stem Cell 22 , — e Burrin, D. Metabolic fate and function of dietary glutamate in the gut. Reeds, P. Intestinal glutamate metabolism. Turnbaugh, P.

An obesity-associated gut microbiome with increased capacity for energy harvest. Soty, M. Gut-brain glucose signaling in energy homeostasis. Cell Metab. Saeidi, N. Reprogramming of intestinal glucose metabolism and glycemic control in rats after gastric bypass. Troy, S.

Intestinal gluconeogenesis is a key factor for early metabolic changes after gastric bypass but not after gastric lap-band in mice.

Montagner, A. Liver PPAR alpha is crucial for whole-body fatty acid homeostasis and is protective against NAFLD. Gut 65 , — Costet, P. Peroxisome proliferator-activated receptor alpha-isoform deficiency leads to progressive dyslipidemia with sexually dimorphic obesity and steatosis.

Coleman, D. A historical perspective on leptin. Med 16 , — Taylor, S. Dietary fructose improves intestinal cell survival and nutrient absorption. Powell, W. Biosynthesis, biological effects, and receptors of hydroxyeicosatetraenoic acids HETEs and oxoeicosatetraenoic acids oxo-ETEs derived from arachidonic acid.

Biochim Biophys. Acta , — Xu, H. Molecular recognition of fatty acids by peroxisome proliferator-activated receptors. Cell 3 , — Caillon, A. The OEA effect on food intake is independent from the presence of PPAR alpha in the intestine and the nodose ganglion, while the impact of OEA on energy expenditure requires the presence of PPAR alpha in mice.

Metabolism 87 , 13—17 Dubois, V. Distinct but complementary contributions of PPAR isotypes to energy homeostasis. Invest , — Hirai, T. Karimian Azari, E. Possible role of intestinal fatty acid oxidation in the eating-inhibitory effect of the PPAR-alpha agonist Wy in high-fat diet fed rats.

PLoS One 8 , e Article ADS PubMed PubMed Central Google Scholar. Bunger, M. Genome-wide analysis of PPARalpha activation in murine small intestine. Genomics 30 , — Fu, J. Oleylethanolamide regulates feeding and body weight through activation of the nuclear receptor PPAR-alpha.

Nature , 90—93 Colin, S. Activation of intestinal peroxisome proliferator-activated receptor-alpha increases high-density lipoprotein production. Heart J. Sato, T. Paneth cells constitute the niche for Lgr5 stem cells in intestinal crypts. Ayehunie, S. Human Primary Cell-Based Organotypic Microtissues for Modeling Small Intestinal Drug Absorption.

Res 35 , 72 Rakhshandehroo, M. Peroxisome proliferator-activated receptor alpha target genes. Beilstein, F. Characteristics and functions of lipid droplets and associated proteins in enterocytes. Cell Res , — Mashek, D. Long-chain acyl-CoA synthetases and fatty acid channeling.

Future Lipido. Article CAS Google Scholar. Diet induced obesity alters intestinal cytoplasmic lipid droplet morphology and proteome in the postprandial response to dietary fat. Front Physiol. Timmers, S. Augmenting muscle diacylglycerol and triacylglycerol content by blocking fatty acid oxidation does not impede insulin sensitivity.

Natl Acad. USA , — Listenberger, L. Adipocyte differentiation-related protein reduces the lipid droplet association of adipose triglyceride lipase and slows triacylglycerol turnover.

Lipid Res 48 , — Robenek, H. Adipophilin-enriched domains in the ER membrane are sites of lipid droplet biogenesis. Cell Sci. Morales, P. Muscle lipid metabolism: role of lipid droplets and perilipins.

Diabetes Res. Frank, D. Perilipin-2 modulates lipid absorption and microbiome responses in the mouse intestine. PLoS One 10 , e Auclair, N. Gastrointestinal factors regulating lipid droplet formation in the intestine. Cell Res , 1—14 Kimura, R.

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Activation of peroxisome proliferator-activated receptor-alpha PPARalpha in proximal intestine improves postprandial lipidemia in obese diabetic KK-Ay mice.

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Fuhrer, T. High-throughput, accurate mass metabolome profiling of cellular extracts by flow injection-time-of-flight mass spectrometry. Download references. At the same time, the relationship of energy expenditure to lean mass was comparable between Maf ΔIEC and control mice Fig.

In agreement with this, Maf ΔIEC mice also had a lower body temperature Fig. Consistently, thermogenic interscapular brown adipose tissue iBAT , but not gonadal white adipose tissue, was reduced in Maf ΔIEC mice, and no compensation for the loss of iBAT mass by, e.

The reduced nutritional phenotype of Maf ΔIEC mice led us to examine the SI in more detail. Overall, we did not observe substantial differences in SI length and villus architecture in the absence of epithelial c-Maf expression Fig.

In line with the absence of c-Maf in secretory IECs, goblet and tuft cell numbers were comparable between Maf ΔIEC and control mice Fig.

However, morphometric measurements of villus height revealed shortening of SI villi in Maf ΔIEC mice, indicative of a reduced absorptive surface area Fig. Collectively, these data demonstrated a reduced nutritional phenotype of Maf ΔIEC mice, suggesting an important role of c-Maf in controlling the nutrient uptake capacity of SI enterocytes.

S2 A isolated from the SI of Maf ΔIEC and control mice. Principal component analysis PCA showed that c-Maf—deficient IECs clustered separately from their WT counterparts, demonstrating a unique role of c-Maf in shaping the transcriptome of IECs Fig.

S2, C and D. We also found many brush-border enzymes responsible for the final stage of carbohydrate and protein digestion, such as Lct , Ace , Ace2 , Anpep , Enpep , Dpp4 , and Mme to be downregulated in c-Maf—deficient IECs Fig.

Consistently, predefined Kyoto Encyclopedia of Genes and Genomes gene sets for carbohydrate and protein digestion and absorption were significantly downregulated in IECs from Maf ΔIEC mice Fig.

Notably, key genes involved in lipid uptake were not differentially regulated in c-Maf—deficient IECs Fig. Importantly, since mRNA—protein correspondence can be poor Maier et al. Additionally, we performed an unbiased proteome screening of c-Maf—deficient and control IECs, which similarly confirmed the broad downregulation of proteins involved in carbohydrate and protein breakdown and transport Fig.

Indeed, despite normal homeostatic blood glucose levels Fig. S2 F , Maf ΔIEC mice exhibited a diminished increase in blood glucose upon oral glucose administration, demonstrating that in vivo intestinal glucose uptake was impaired in these mice Fig.

Similarly, we also checked amino acid concentrations in blood serum as a read-out of in vivo protein uptake. However, systemic amino acid concentrations were not altered in Maf ΔIEC mice in steady state Fig. Therefore, we tested amino acid uptake with a more simplistic experimental approach.

Ex vivo incubation of primary SI IECs with the fluorescently labeled amino acid biotracker FITC-Cystine Siska et al. Likewise, we detected impaired ex vivo uptake of FITC-Cystine into intact SI tissue from Maf ΔIEC mice by IF Fig.

Using the same assay, we also found the fluorescently labeled dipeptide D-Ala-Lys-AMCA to be taken up less efficiently into c-Maf—deficient IECs Fig.

S2 H and Table S2. Collectively, these data demonstrated that SI enterocytes required c-Maf to globally express gene programs essential for carbohydrate and protein uptake.

Consequently, c-Maf deficiency impaired the capacity of SI enterocytes to absorb these essential nutrients. Enterocytes are capable of dynamically adapting their gene expression profile to different nutrient availability, thereby enabling flexible and efficient nutrient uptake Diamond and Karasov, ; Sullivan et al.

Therefore, we asked whether enterocytes also required c-Maf to sense and adapt to selective nutrient availability. In contrast, despite being consistently downregulated in Maf ΔIEC mice, the expression of several peptides and amino acid transporters was largely unaffected by dietary protein availability, as previously shown Fig.

S3 A ; Sullivan et al. Based on this concept, we explored whether epithelial c-Maf deficiency somehow affected this IEC—lymphocyte circuit. However, immune cell phenotyping of SI LP lymphocytes did not show quantitative differences in γδ T cells and ILC3s, as well as in ILC3-derived IL production between Maf ΔIEC mice and littermate controls Fig.

Yet, we found intraepithelial lymphocytes IELs to be less abundant within the c-Maf—deficient epithelium Fig. Further characterization of Maf ΔIEC IELs did not reveal differences in subset composition Fig. S3 C or expression of genes determining cell proliferation and survival Fig.

However, the IEL chemoattractant Cxl10 was significantly downregulated in c-Maf—deficient IECs Table S1 ; Shibahara et al. Functionally, Maf ΔIEC IELs exhibited reduced expression of Grzmb , but not of Ifng , Tnfa , and Il17 , as compared to IELs from controls Fig.

In summary, our data identified c-Maf as a central regulator of the molecular adaptation of SI enterocytes to the nutritional environment. Importantly, homeostatic intestinal immunity was largely uncompromised by epithelial c-Maf deficiency, except for SI IELs, which were quantitatively and qualitatively reduced in Maf ΔIEC mice.

As diet and nutrition have emerged as pivotal determinants of gut microbiota composition Dahl et al. Indeed, our RNA-Seq data from c-Maf—deficient IECs Fig. Indeed, quantitative PCR qPCR from ileal mucosal samples and bacterial FISH analysis demonstrated a substantial increase in the abundance of SFB in Maf ΔIEC mice Fig.

Interestingly, SFB in Maf ΔIEC mice also showed differences in morphology, exhibiting long segmented filaments, while SFB in control animals had fewer segments and appeared stubble-like Fig. Thus, intestinal epithelial c-Maf expression was also essential for the containment of a key commensal bacterium, which has coevolved to intimately associate with the gut epithelium.

Due to their reduced genome, SFB are known to highly depend on their host for essential nutrients Sczesnak et al. Therefore, superior access to luminal nutrients caused by incomplete nutrient uptake in Maf ΔIEC mice might serve as an explanation for the overgrowth of SFB.

Despite the downregulation of genes involved in nutrient uptake, our RNA-Seq data showed that c-Maf deficiency also globally perturbed the differentiation and functional zonation of SI enterocytes Moor et al.

Zonation clusters based on the spatial gene expression profiles of enterocytes along the SI villus axis were significantly dysregulated in Maf ΔIEC mice Fig.

Specifically, crypt- and bottom-villus gene clusters cluster 1 and 2 were upregulated, whereas mid- and top-villus gene clusters cluster 3 [including c-Maf], 4, and 5 were downregulated in Maf ΔIEC IECs Fig. Importantly, the de-enrichment of mid- and top-villus gene clusters was paralleled by downregulation of signature genes for mature enterocytes, whereas genes specific for immature enterocytes were upregulated in IECs from Maf ΔIEC mice Fig.

Thus, SI enterocytes required c-Maf expression to appropriately mature and differentiate along the villus axis. The perturbations in enterocyte maturation and zonation in Maf ΔIEC mice prompted us to analyze the role of c-Maf for enterocyte differentiation more closely. In vitro modeling of IEC differentiation using small intestinal organoids demonstrated that c-Maf was dispensable for overall organoid growth, and viability as assessed by crypt expansion and morphology of c-Maf—deficient and control organoids Fig.

Further, qPCR analysis of organoids confirmed the broad downregulation of carbohydrate and protein transporters in the absence of c-Maf, supporting a cell-intrinsic and direct role of c-Maf in the regulation of these genes Fig. S3, F and G. Consistent with the absence of c-Maf expression in epithelial crypts, c-Maf—deficient organoids showed unaltered expression of stem cell-related genes, Lgr5 and Cd44 Fig.

However, we detected diminished expression of Alpi , a marker for mature enterocytes, while Hes1 , which labels absorptive progenitor cells, was not differentially expressed in Maf ΔIEC organoids Fig.

Collectively, these results indicated that c-Maf was essential to license SI enterocyte maturation and differentiation. Without c-Maf, enterocytes remained in an immature state and exhibited a skewed zonation profile.

Accordingly, a recent study by Petrova and colleagues in this issue similarly reported a role for c-Maf in maintaining enterocyte zonation González-Loyola et al. Interestingly, in their study, inducible deletion of c-Maf in IECs in adult mice additionally disrupted the balance between SI enterocytes and secretory cell types, thereby impairing the regenerative epithelial response to acute intestinal injury.

Thus, overall, the precisely timed BMP-mediated upregulation of c-Maf expression in newly formed enterocytes exiting the crypt represents a key step in their developmental trajectory. In this manner, c-Maf facilitates the spatial and functional specialization of enterocytes, including the acquisition of gene programs controlling intestinal nutrient uptake.

To generate conditional c-Maf—deficient mice Maf ΔIEC , Vil-Cre mice Madison et al. Diefenbach, Berlin, Germany were crossed to Maf-flox mice Wende et al.

Diefenbach, Berlin, Germany. Germ-free mice were kindly provided by Ahmed Hegazy, Berlin, Germany. All mice used were 7—10 wk old. Body weight and temperature were determined using a laboratory scale and an infrared thermometer FTC.

All animal experiments were in accordance with the ethical standards of the institution or practice at which the studies were conducted and were reviewed and approved by the responsible ethics committees of Germany LAGeSo.

For the determination of body composition, fat and lean mass were assessed by 1H-magnetic resonance spectroscopy using a Minispec LF50 Body Composition Analyzer Bruker BioSpin. Basal metabolic parameters were analyzed in a TSE LabMaster System TSE Systems. Mice were acclimated to the metabolic cages individually housed 8 h before starting and supplied with regular diet.

Calorimetry was performed with a computer-controlled open circuit calorimetry system composed of 10 metabolic cages. Each cage was equipped with a special water bottle and a food tray connected to a balance as well as an activity monitor.

Parameters were measured for each mouse at 2. Energy expenditure was adjusted for mouse body weight. Data were analyzed as described Tschӧp et al. IECs were isolated using an adapted protocol from Gracz et al. Briefly, small intestinal tissue was collected, cut longitudinally, and washed two times in cold PBS before incubating in PBS containing 30 mM EDTA and 1.

The tissue was then transferred to PBS containing 30 mM EDTA and incubated under constant stirring for 10 min at 37°C. RNA was isolated with the RNeasy Micro Kit from Qiagen according to the manufacturer's protocol.

RNA libraries were generated and sequencing was performed by Novogene Cambridge, UK. Three biological replicates of each genotype were sequenced. featureCounts v1. Differential gene expression data were plotted as MA plots using Prism 9 software GraphPad and for selected genes as heatmaps using Morpheus software Broad Institute.

The RNA-Seq data have been deposited to the NCBI GEO platform GSE GSEA was performed using the GSEA tool from the Broad Institute Subramanian et al. Gene sets used in this study were taken from the Kyoto Encyclopedia of Genes and Genomes database or published studies Haber et al.

Serum samples were defrosted, diluted with the extraction solvent, and agitated for 10 min at 1, rpm at room temperature RT; Thermomix Eppendorf. All samples and standards were cooled on ice for 20 min before insoluble matter was removed by centrifugation 2 min, 4°C, 16, rcf.

Amino acids were resolved on a Waters ACQUITY UPLCBEH Amide column 2. Column temperature was 25°C, flow rate 0. Precise source settings and multiple reaction monitoring transitions can be provided upon request.

Compounds were identified by matching retention times and fragmentation patterns with analytical pure standards. Data analysis was performed with Agilent Masshunter software. Signals were integrated and quantified by calibrating with the ratios of natural to isotope-labeled internal standards and adjusted for dilution.

Serum amino acid concentrations are reported in micromolars. IECs were resuspended in µl radioimmunoprecipitation assay RIPA buffer with protease inhibitor and shaken at RT for 15 min Eppendorf thermomixer at rpm. Mouse liver was homogenized in M-Tubes ; Miltenyi Biotec with 5 ml RIPA buffer and protease inhibitor in a GentleMacs instrument.

The protein concentration was determined ; Pierce Protein Assay Kit , and a volume corresponding to 25 µg was transferred to a TwinTec plate Eppendorf , topped up to 50 µl with RIPA before SP3 protein digestion on a Beckmann Biomek i7 workstation as previously described with one-step reduction and alkylation Muller et al.

Briefly, The samples were incubated for 18 min before placing on a magnetic rack for 3 min to pull down the beads with protein. The reaction was stopped by adding formic acid to a final concentration of 0.

Peptide separation was accomplished in a min water to acetonitrile gradient solvent A: 0. The Orbitrap worked in centroid mode with a duty cycle consisting of one MS1 scan at 70, resolution with maximum injection time ms and 3e6 AGC target followed by 40 variable MS2 scans using an 0.

The window length started with 25 MS2 scans at MS source settings were as follows: spray voltage 2. The raw data was processed using DIA-NN 1. MS2 and MS1 mass accuracies were both set to 15 ppm and the scan window size was automatically optimized. DIA-NN was run in library-free mode with standard settings fasta digest and deep learning-based spectra, retention time and ion mobility prediction using the Uniprot mouse reviewed Swiss-Prot, downloaded on annotations UniProt Consortium, and the match-between-runs option.

Peptide normalized intensities were subjected to quality control with all samples passing acceptance criteria. The missing values of remaining peptides were imputed group-based using the PCA method Josse and Husson, Normalization was performed with LIMMA Ritchie et al.

Statistical analysis of proteomics data was carried out using internally developed R scripts based on publicly available packages. Linear modeling was based on the R package LIMMA Ritchie et al. The categorical factor Class had two levels: Ctrl and Maf ΔIEC IECs.

For finding regulated features, the following criteria were applied: significance level α was set to 0. The log fold-change criterion was applied to guarantee that the measured signal is above the average noise level.

Functional GSEA analysis was carried out using R package clusterProfiler Yu et al. The mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium via the PRIDE Perez-Riverol et al. Maf ΔIEC and littermate control mice were fasted for 7 h with water ad libitum. Then the body weight of the mice was measured and a total volume in µl of 7.

The amount of glucose in blood was measured before and 30 and 60 min after gavage with a glucometer ACCU-CHEK Mobile.

SI tissue was treated with HBSS buffer without calcium and magnesium containing 5 mM EDTA and 10 mM Hepes pH 7. The supernatant was filtered, and the remaining tissue was mashed through a μm mesh.

Recovered cells were counted and stained with different antibodies Table S4. For flow cytometry, cells were stained with surface antibodies including a viability dye suitable for fixation if required at 4°C for 20 min. Lineage includes anti-CD5, anti-CD8α, anti-CD3, anti-Gr-1, anti-TCRγδ, anti-FcεRIα, anti-CD19, and anti-CD11c.

Cells were acquired with a BD LSRFortessa X, and analysis was performed with FlowJo Tree Star software. To measure the uptake of Cystine by primary epithelial cells, IECs were isolated as described above and incubated with 5 µM BioTracker FITC-Cystine Sigma-Aldrich for 15 min in PBS.

The SI was isolated from Maf ΔIEC and littermate control mice. Afterward, a section of 7 cm of distal small intestine was longitudinally cut and thoroughly washed in cold PBS followed by incubation in PBS containing 5 µM BioTracker FITC-Cystine Sigma-Aldrich for 15 min or 25 µM D-Ala-Lys-AMCA Hycultec for 10 min at 37°C with constant horizontal agitation at rpm.

Finally, nuclei were stained with DAPI for 30 min at RT in combination with FITC-Cystine assay, or with Helix NP Green BioLegend for 15 min at RT in combination with D-Ala-Lys-AMCA assay.

Images were taken on a Zeiss Axio Observer 7 Carl Zeiss and analyzed with ImageJ. For organoid cultures, 20 cm of the proximal SI was collected, cut longitudinally, and washed two times with cold PBS. The tissue was cut into 2-mm pieces, placed in cold PBS containing 5 mM EDTA, and pipetted up and down 10 times with a disposable pipette coated with 0.

Then supernatant was discarded, and the tissue was incubated twice in 5 mM EDTA in PBS for 10 and 30 min at 4°C with constant agitation. After EDTA solution removal, fresh PBS was added and the tissue was pipetted up and down 15 times with a disposable pipette coated with 0.

This procedure was repeated four more times to obtain a total of five fractions. The fraction with higher crypt enrichment was identified under the microscope and passed through a µm cell strainer.

For Noggin removal experiments, organoids were cultured in ENR medium for 2 d and then ENR was substituted for ER ENR without Noggin.

For crypt expansion index, images of Maf ΔIEC and control organoids were taken for 4 consecutive days after seeding. Buds and total organoids were then counted at least 40 organoids per well using ImageJ software, and crypt expansion index was calculated and shown as the number of crypts per organoid.

mRNA from sorted cells was isolated with the RNeasy Plus Micro Kit according to the manual of the manufacturer QIAGEN. RNA from cell suspensions, organoids, or tissues was extracted using TRIzol reagent following the protocol from ImmGen Heng et al.

The isolated RNA was quantified using Nanodrop before qPCR performance. For IF staining, 5—7 cm of the distal jejunum were taken and Swiss rolls were prepared as previously described with minor adaptations Bialkowska et al. Compound Tissue-Tek, Sakura , and frozen with liquid nitrogen.

blocks were cut into 5-µm sections for IF or conventional periodic acid—Schiff staining. For c-Maf, DCLK1, ChgA, and UEA1 staining, first, slides were rehydrated in cold PBS, then blocked and permeabilized in 0.

Next, slides were incubated with c-Maf antibody in blocking buffer at RT overnight. Then slides were cooled down at RT for 30 min and washed three times in PBS and blocked and permeabilized in blocking buffer at RT for 1 h. Next, primary antibody staining was performed at RT for 1 h in blocking buffer.

Finally, slides were stained with secondary antibodies and DAPI in blocking solution at RT for 1 h and mounted with ProLong Diamond Antifade Mountant Thermo Fisher Scientific. Images were taken on a confocal microscope LSM Carl Zeiss , a Zeiss Axio Observer 7 Carl Zeiss , and analyzed with ImageJ.

For the quantification of SFB, ileal mucosal DNA was isolated. To specifically isolate the DNA from ileal mucosa, 2 cm of the ileum was taken, cut longitudinally, and washed thoroughly in cold PBS to remove the fecal content.

The clean tissue was washed thoroughly in 0. Bacterial DNA was then isolated from mucosal content with the ZymoBIOMICS DNA Miniprep Kit Zymo Research , and bacterial load was measured by qPCR.

The SFB abundance is presented relative to the abundance of eubacteria. RNA-FISH for SFB was performed as previously described Johansson and Hansson, Images were taken on Zeiss Axio Observer 7 Carl Zeiss and processed using ImageJ.

qPCR was performed using a Quant Studio 5 system Applied Biosystems and the SYBR Green PCR Master Mix Kit Applied Biosystems. The mRNA expression is presented relative to the expression of the housekeeping gene hypoxanthine-guanine phosphoribosyltransferase.

Real-time qPCR primer used in this study can be found in Table S3. A list of antibodies used in this study is provided in Table S4. Data are represented as the means with SEM and summarize or are representative of independent experiments as specified in the text.

Statistical analysis was performed using Prism 9 software GraphPad with two-tailed unpaired Student's t test except RNA-Seq data. S1 shows data, which demonstrate that intestinal epithelial c-Maf expression is driven by BMP signaling.

S2 confirms that the expression of epithelial carbohydrate and protein transporters is reduced in Maf ΔIEC mice. S3 shows that c-Maf—deficient organoids also express reduced levels of carbohydrate and protein transporters.

Table S1 shows DE genes between c-Maf—deficient and control IECs as identified by RNA-Seq. Table S2 shows differentially expressed proteins between c-Maf—deficient and control IECs and liver tissue as identified by proteomics.

Table S3 shows real-time qPCR primers used in this study. Table S4 lists all antibodies used in this study. We thank Andreas Diefenbach Charité — Universitätsmedizin Berlin, Germany for discussion, providing key resources, and proofreading the manuscript.

We further thank Efstathios Stamatiades, Stylianos Gnafakis, Omer Shomrat, Manuela Stäber, Kathrin Textoris-Taube, Roodline Cineus, Ahmed Hegazy, and Frederik Heinrich for resources and technical and experimental help.

The Benjamin Franklin Flow Cytometry Facility and the Core Facility High Throughput Mass Cytometry at Charité — Universitätsmedizin Berlin are greatly acknowledged for cell sorting and proteomics analysis, respectively.

In addition, we thank Dr. Anja A. Kühl and the iPATH facility at Charité — Universitätsmedizin Berlin for support in the preparation of histological samples and staining, the Central Biobank Charité — Universitätsmedizin Berlin for slide scanning and digitalization, and Jörg Piontek for technical support with confocal microscopy.

This research was supported by the Deutsche Forschungsgemeinschaft Priority Program to C. Neumann , by the Ministry of Education and Research as part of the National Research Node "Mass spectrometry in Systems Medicine" under grant agreement L to M.

Author contributions: C. Cosovanu designed and performed most experiments, analyzed data, generated figures, and helped writing the manuscript.

Resch helped with experimental design and execution. Jordan assisted in feeding experiments. Lehmann was responsible for sample preparation for metabolomics and LC-MS instrumentation.

Ralser provided funding for personnel and analytical instruments. Farztdinov performed bioinformatic data analysis and presentation of proteomic data. Mülleder supervised MS measurements and was responsible for MS data analysis and management.

Spranger and S. Brachs supervised metabolic analysis NMR, metabolic cages and provided reagents and equipment for their execution. Neumann conceived the project, designed and performed experiments, analyzed data, generated figures, and wrote the manuscript.

All coauthors read, commented on, and approved the manuscript. shows differentially expressed proteins between c-Maf—deficient and control IECs and liver tissue as identified by proteomics. c-Maf expression marks mature SI enterocytes of the mid-villus region.

A Schematic representation of the murine gastrointestinal tract depicting distinct intestinal segments. Representative flow cytometric plots of EpCAM vs.

c-Maf staining are shown. Numbers in the plots indicate percentage. Scale bar, 50 µm. E Maf expression among distinct SI IEC subsets as determined by scRNA-Seq Haber et al. F Intensity of c-Maf IF staining along the SI crypt—villus axis.

Data are representative of at least two independent experiments. Intestinal epithelial c-Maf expression is driven by BMP signaling. B SI organoid cultures from Maf ΔIEC and littermate control mice were cultured in ENR medium for 2 d.

Afterwards, ENR was refreshed or substituted for ER ENR without Noggin medium. In addition, organoids were stimulated with BMP-4 for 6 h at day 4 of culture before organoids were harvested for qPCR analysis.

Statistical differences were tested using an unpaired Student's t test two-tailed. Maf ΔIEC mice exhibit a reduced nutritional phenotype. A Representative IF staining of c-Maf and DAPI on cross-section of the SI of Maf ΔIEC and control mice.

B Analysis of c-Maf expression in SI IECs from Maf ΔIEC and control mice. E Regression plot of energy expenditure EE vs. K Representative periodic acid—Schiff staining on cross-section of the SI of Maf ΔIEC and control mice.