《人体的社交网络——共生微生物》课外文献阅读：Gut Microbiota Orchestrates Energy Homeostasis during Cold.pdf

Cell Article Gut Microbiota Orchestrates Energy Homeostasis during cold Claire Chevalier, 1,2,8 Ozren Stojanovic, .2.,8 Didier J. Colin, Nicolas Suarez- Zamorano, 1,21 Tarallo, 1.2 Christelle Veyrat-Durebex, 2 Dorothee Rigo, 2 Salvatore Fabbiano, ,2 Ana Stevanovic, ,2 Hagemann, 4 Xavier Montet, Yann Seimbille, 3 Nicola Zamboni, Siegfried Hapfelmeier, and Mirko Trajkovski",2, 7. Department of Cell Physiology and Metabolism, Centre Medical Universitaire(CMU), Faculty of Medicine, University of Geneva, 1211 Diabetes Centre, Faculty of Medicine, University of Geneva, 1211 Geneva, Switzerland cEntre for BioMedical Imaging(CIBM), Geneva University Hospitals, 1211 Geneva, Switzerland aInstitute for Infectious Diseases, University of Bem, 3010 Bern, Switzerland SDivision of Radiology, Geneva University Hospitals, 1211 Geneva, Switzerland iNstitute for Molecular Systems Biology, Swiss Federal Institute of Technology(ETH) Zurich, 8093 Zurich, Switzerland "Division of Biosciences, Institute of Structural and Molecular Biology University College London(UCL, London WClE 6BT, UK 8Co-first author Correspondence: mirko trajkovski@unige. ch http://dx.doi.org/10.1016/.cell.2015.11.004 SUMMARY leads to elevated intracellular cyclic AMP (Cannon and Neder gaard, 2004) Young et al., 1984). The BAT is present at distinct Microbial functions in the host physiology are a result anatomical sites, including the interscapular, perirenal, and axil- of the microbiota- host co-evolution We show that lary depots. brown fat cells also emerge in subcutaneous WAT cold exposure leads to marked shift of the microbiota (SAT)(known as"beige"cells)in response to cold or exercise composition, referred to as cold microbiota. Trans- Cousin et al, 1992)(Guerra et al 2001), a process referred to plantation of the cold microbiota to germ-free mice as wAT browning. Loss of BAT function is linked to obesity is sufficient to increase insulin sensitivity of the and metabolic diseases (owell et al.,1993).Promotion of host and enable tolerance to cold partly by promot- increased BAT development, on the other hand, increases EE without causing dysfunction in other and is associated ing the white fat browning, leading to increased en- with a lean and healthy phenotype(Ghorbani et al.1997; Guerra ergy expenditure and fat loss. During prolonged et al, 1998; Kopecky et al, 1995), suggesting the manipulation of cold, however, the body weight loss is attenuated, the fat stores as an important therapeutic objective caused by adaptive mechanisms maximizing caloric The gastrointestinal tract is the body's largest endocrine organ uptake and increasing intestinal, villi, and microvilli that releases a number of regulatory peptide hormones that influ- lengths. This increased absorptive surface is trans- ence many physiological processes(Badman and Flier, 2005) ferable with the cold microbiota, leading to altered The intestinal epithelium undergoes rapid self-renewal fueled intestinal gene expression promoting tissue remod- by multipotent Lgr5-expressing stem cells located in the crypts eling and suppression of apoptosis-the effect of Lieberkuhn and is terminated by apoptosis/exfoliation of diminished by co-transplanting the most cold-down regulated strain Akkermansia muciniphila during the (Sato et al., 2009). At the apical surface, the epithelial cells cold microbiota transfer. Our results demonstrate the have microvilli that further substantially increase the absorptive area and mediate the secretory functions. The intestinal micro- microbiota as a key factor orchestrating the overall biota co-develops with the host, and its composition is influ- energy homeostasis during increased demand enced by several physiological changes (Koren et al., 2012 Liou et al., 2013: Ridaura et al., 2013). The colonization starts INTRODUCTION immediately after birth and is initially defined by the type of de- livery and early feeding. After 1 year of age, the intestinal mi- Food intake, energy expenditure(EE, and body adiposity are ho- crobiota is already shaped and stabilized but continues to be meostatically regulated, and malfunctions of this balance can influenced by environmental factors including diet (Sekirov cause obesity(Murphy and Bloom, 2006)(Farooqi and O'Rahilly, et al., 2010). A wide range of pathologies have been associated 005). Mammalian white adipose tissue(WAT) is an important with alterations of the gut microbial composition(e. g, asthma regulator of the whole body homeostasis that stores energy in arthritis, autism, or obesity)(Sommer and Backhed, 2013).The form of triglycerides (TGs). The brown adipose tissue(BAT) intestinal microbiota can also influence the whole-body meta- catabolizes lipids to produce heat, function mediated by the tis- bolism by affecting energy balance(Backhed et al, 2004) ue-specific uncoupling protein 1(Ucp1)abundantly present in (Chou et al., 2008)(Turnbaugh et al., 2006)(Koren et al., 2012) the BAt mitochondria. bat differentiation can be induced by (Ridaura et al., 2013). The mechanisms and the nature of the prolonged cold exposure and beta-adrenergic stimulation that phenotypic and morphological changes that regulate the energy 360 Cell 163. 1360-1374 December 3. 2015 2015 Elsevier Inc

Article Gut Microbiota Orchestrates Energy Homeostasis during Cold Claire Chevalier,1,2,8 Ozren Stojanovic, ! 1,2,8 Didier J. Colin,3 Nicolas Suarez-Zamorano,1,2 Valentina Tarallo,1,2 Christelle Veyrat-Durebex,1,2 Dorothe´ e Rigo,1,2 Salvatore Fabbiano,1,2 Ana Stevanovic, ! 1,2 Stefanie Hagemann,4 Xavier Montet,5 Yann Seimbille,3 Nicola Zamboni,6 Siegfried Hapfelmeier,4 and Mirko Trajkovski1,2,7,* 1Department of Cell Physiology and Metabolism, Centre Me´ dical Universitaire (CMU), Faculty of Medicine, University of Geneva, 1211 Geneva, Switzerland 2Diabetes Centre, Faculty of Medicine, University of Geneva, 1211 Geneva, Switzerland 3Centre for BioMedical Imaging (CIBM), Geneva University Hospitals, 1211 Geneva, Switzerland 4Institute for Infectious Diseases, University of Bern, 3010 Bern, Switzerland 5Division of Radiology, Geneva University Hospitals, 1211 Geneva, Switzerland 6Institute for Molecular Systems Biology, Swiss Federal Institute of Technology (ETH) Zurich, 8093 Zurich, Switzerland 7Division of Biosciences, Institute of Structural and Molecular Biology, University College London (UCL), London WC1E 6BT, UK 8Co-first author *Correspondence: mirko.trajkovski@unige.ch http://dx.doi.org/10.1016/j.cell.2015.11.004 SUMMARY Microbial functions in the host physiology are a result of the microbiota-host co-evolution. We show that cold exposure leads to marked shift of the microbiota composition, referred to as cold microbiota. Transplantation of the cold microbiota to germ-free mice is sufficient to increase insulin sensitivity of the host and enable tolerance to cold partly by promoting the white fat browning, leading to increased energy expenditure and fat loss. During prolonged cold, however, the body weight loss is attenuated, caused by adaptive mechanisms maximizing caloric uptake and increasing intestinal, villi, and microvilli lengths. This increased absorptive surface is transferable with the cold microbiota, leading to altered intestinal gene expression promoting tissue remodeling and suppression of apoptosis—the effect diminished by co-transplanting the most cold-downregulated strain Akkermansia muciniphila during the cold microbiota transfer. Our results demonstrate the microbiota as a key factor orchestrating the overall energy homeostasis during increased demand. INTRODUCTION Food intake, energy expenditure (EE), and body adiposity are homeostatically regulated, and malfunctions of this balance can cause obesity (Murphy and Bloom, 2006) (Farooqi and O’Rahilly, 2005). Mammalian white adipose tissue (WAT) is an important regulator of the whole body homeostasis that stores energy in form of triglycerides (TGs). The brown adipose tissue (BAT) catabolizes lipids to produce heat, function mediated by the tissue-specific uncoupling protein 1 (Ucp1) abundantly present in the BAT mitochondria. BAT differentiation can be induced by prolonged cold exposure and beta-adrenergic stimulation that leads to elevated intracellular cyclic AMP (Cannon and Nedergaard, 2004) (Young et al., 1984). The BAT is present at distinct anatomical sites, including the interscapular, perirenal, and axillary depots. Brown fat cells also emerge in subcutaneous WAT (SAT) (known as ‘‘beige’’ cells) in response to cold or exercise (Cousin et al., 1992) (Guerra et al., 2001), a process referred to as WAT browning. Loss of BAT function is linked to obesity and metabolic diseases (Lowell et al., 1993). Promotion of increased BAT development, on the other hand, increases EE without causing dysfunction in other tissues and is associated with a lean and healthy phenotype (Ghorbani et al., 1997; Guerra et al., 1998; Kopecky et al., 1995), suggesting the manipulation of the fat stores as an important therapeutic objective. The gastrointestinal tract is the body’s largest endocrine organ that releases a number of regulatory peptide hormones that influence many physiological processes (Badman and Flier, 2005). The intestinal epithelium undergoes rapid self-renewal fueled by multipotent Lgr5-expressing stem cells located in the crypts of Lieberkuhn and is terminated by apoptosis/exfoliation of terminally differentiated cells at the tips of small intestinal villi (Sato et al., 2009). At the apical surface, the epithelial cells have microvilli that further substantially increase the absorptive area and mediate the secretory functions. The intestinal microbiota co-develops with the host, and its composition is influenced by several physiological changes (Koren et al., 2012; Liou et al., 2013; Ridaura et al., 2013). The colonization starts immediately after birth and is initially defined by the type of delivery and early feeding. After 1 year of age, the intestinal microbiota is already shaped and stabilized but continues to be influenced by environmental factors including diet (Sekirov et al., 2010). A wide range of pathologies have been associated with alterations of the gut microbial composition (e.g., asthma, arthritis, autism, or obesity) (Sommer and Ba¨ ckhed, 2013). The intestinal microbiota can also influence the whole-body metabolism by affecting energy balance (Ba¨ ckhed et al., 2004) (Chou et al., 2008) (Turnbaugh et al., 2006) (Koren et al., 2012) (Ridaura et al., 2013). The mechanisms and the nature of the phenotypic and morphological changes that regulate the energy 1360 Cell 163, 1360–1374, December 3, 2015 ª2015 Elsevier Inc

R5.31 R2.31 R4.31 R6.31 R1.31 R3.31 C5.31 C6.31 C1.31 C8.31 C4.31 C2.31 C3.31 C7.31 Firmicutes;Clostridia;Clostridiales;91otu10234 Verrucomicrobia;Verrucomicrobiae;Verrucomicrobiales;Verrucomicrobiac. Firmicutes;Clostridia;Clostridiales;Christensenellaceae Actinobacteria;Coriobacteriia;Coriobacteriales;Coriobacteriaceae Firmicutes;Erysipelotrichi;Erysipelotrichales;Erysipelotrichaceae Bacteroidetes;Bacteroidia;Bacteroidales;Porphyromonadaceae Firmicutes;Clostridia;Clostridiales;91otu14680 Firmicutes;Bacilli;Lactobacillales;Streptococcaceae Bacteroidetes;Bacteroidia;Bacteroidales;[Odoribacteraceae] Proteobacteria;Alphaproteobacteria;RF32;91otu6104 Firmicutes;Clostridia;Clostridiales;91otu16967 Firmicutes;Clostridia;Clostridiales;91otu5188 Firmicutes;Clostridia;Clostridiales;91otu14676 Firmicutes;Clostridia;Clostridiales;91otu6640 Firmicutes;Clostridia;Clostridiales;91otu6340 Firmicutes;Clostridia;Clostridiales;91otu8083 Firmicutes;Clostridia;Clostridiales;91otu9255 Firmicutes;Clostridia;Clostridiales;91otu5878 Firmicutes;Clostridia;Clostridiales;91otu14543 Firmicutes;Clostridia;Clostridiales;91otu7553 Firmicutes;Clostridia;Clostridiales;91otu10543 Firmicutes;Clostridia;Clostridiales;91otu16941 Firmicutes;Clostridia;Clostridiales;91otu5473 Firmicutes;Clostridia;Clostridiales;91otu5977 Firmicutes;Clostridia;Clostridiales;91otu15800 Firmicutes;Clostridia;Clostridiales;91otu21549 Firmicutes;Clostridia;Clostridiales;91otu1083 Firmicutes;Clostridia;Clostridiales;91otu7098 Firmicutes;Clostridia;Clostridiales;91otu5626 Firmicutes;Clostridia;Clostridiales;91otu5842 Firmicutes;Clostridia;Clostridiales;91otu4292 Firmicutes;Clostridia;Clostridiales;91otu4244 Bacteroidetes;Bacteroidia;Bacteroidales;S24−7 Bacteroidetes;Bacteroidia;Bacteroidales;Rikenellaceae Firmicutes;Clostridia;Clostridiales;Ruminococcaceae Proteobacteria;Betaproteobacteria;Burkholderiales;Alcaligenaceae Bacteroidetes;Bacteroidia;Bacteroidales;Bacteroidaceae Firmicutes;Clostridia;Clostridiales;91otu8259 Deferribacteres;Deferribacteres;Deferribacterales;Deferribacteraceae Firmicutes;Clostridia;Clostridiales;Dehalobacteriaceae Firmicutes;Clostridia;Clostridiales;Lachnospiraceae Proteobacteria;Deltaproteobacteria;Desulfovibrionales;Desulfovibrionac. 012345 Log10 Abundance –8 –6 –4 –2 0 2 *** * 4 8 ∆°C compared to To Time (hrs) 0 4 8 30 32 34 36 38 40 *** * Body temperature (C°) Ad libitum No food 32 34 36 38 40 Body temperature (C°) Control males Abx males * 0 3 * Body temperature (C°) 0 4 24 * * 0.00 0.25 0.50 0.75 1.00 RT Cold fraction of sample taxon Bacteroidetes Firmicutes Verrucomicrobia Proteobacteria Deferribacteres Tenericutes Cyanobacteria Actinobacteria other Cecum Feces Phylum-level proportional abundance 0.5 0.6 0.7 0.8 0.9 Firmicutes *** 0.0 0.1 0.2 0.3 0.4 Bacteroidetes *** 0.00 0.01 0.02 0.03 0.04 0.05 Proteobacteria * 0.00 0.01 0.02 0.03 Ternericutes 0.000 0.005 0.010 0.015 Act nob i acter a i *** 0.000 0.002 0.004 0.006 0.008 0.010 Deferr bi acter ai * RT D0 RT D11 RT D31 Cold D0 0.000 0.002 0.004 0.006 0.008 0.010 Verrucomicrob ai ** 0.000 0.002 0.004 0.006 0.008 Cyanobacteria * Phylum richness feces (%/100) 0.55 0.60 0.65 0.70 0.75 0.80 0.20 0.25 0.30 0.35 0.00 0.01 0.02 0.03 0.04 0.000 0.005 0.010 0.015 0.020 0.000 0.005 0.010 0.015 0.020 0.000 0.001 0.002 0.003 0.004 0.005 RT Cold 0.000 0.002 0.004 0.006 0.008 0.010 *** RT Cold 0.0010 0.0012 0.0014 0.0016 0.0018 Firmicutes Bacteroidetes Proteobacteria Ternericutes Actinobacteria Deferribacteria Verrucomicrobia Cyanobacteria * * Phylum richness cecum (%/100) −1.452 −0.972 −0.492 1.02 2.04 3.063 Phylum color ranges Actinobacteria Verrucomicrobia Proteobacteria Firmicutes Tenericutes Deferribacteres Bacteroidetes 245324 178331 2897325 4420206 265483 210073 239562 17822 259870 422727 3392847 265280 1108378 307416 4435561 260756 233817 180919 2901246 266343 267743 276029 262541 309054 346595 261064 263612 797021 6345534 169845 259006 179265 229459 1108078 586453 176868 4425214 4474173 276236 2645488 4374042 3588390 174573 801260 4449518 4331760 4372003 4339144 437137 325850 Cold RT 0 Heatmap level ∆°C compared to To 4 24 * * −0.10 −0.05 0.00 0.05 0.10 −0.4 −0.2 0.0 0.2 0.4 PCoA 1 [86.9%] PCoA 2 [4.2%] A BC D E F G H I JK RT Cold 32 34 36 38 40 Control females Abx females –4 –3 –2 –1 0 1 2 RT Cold Time (hrs) Cold Day0 Cold Day11 Cold Day31 RT Day31 Cold D11 Cold D31 RT D0 RT D11 RT D31 Cold D0 Cold D11 Cold D31 (legend on next page) Cell 163, 1360–1374, December 3, 2015 ª2015 Elsevier Inc. 1361

Cell tion remain poorly understood. Here, we show that the micro- controls. Profiling of the microbiota composition by 16S rRNA biota remodeling is an important contributor of the beige fat gene sequencing followed by principal coordinates analysis induction during cold and a key factor that promotes energy up-(PCoA) based on weighted UniFrac distance, showed major al- ke by increasing the intestinal absorptive area, thus orches- terations of the microbiota content both in cecum and feces trating the overall energy homeostasis during increased energy samples of cold-exposed animals(Figures 1F, S2A, and S2B) As expected, Firmicutes was the richest phylum in all samples n average 69.10%)(Figures 1I and 1J). Bacteroidetes was RESULTS the most abundant phylum(on average 63. 50%)in all samples except the cold-exposed day 31 samples(Figures S2C-S2E) Cold Exposure Changes the Gut Microbiota We observed differences in operational taxonomic units(OTUs) Composition abundance at phylum level in Bacteroidetes, Firmicutes, Verru Short-term cold exposure for up to 10 days leads to increased comicrobia, Deferribacteres, Cyanobacteria, and Actinobacte- EE relative to the energy uptake and suppresses BW and white ria, and differences in oTU numbers at phylum-level in all the fat mass gain(Figures S1A-S1F)(u et al., 2012, 2013). To above plus Deferribacteres based on factor summary bar chart investigate the importance of the acutely consumed food and Individual species, or family-based hierarchical clustering using caloric harvest during cold exposure, we restricted the food ac- the average-neighbor method, confirmed the major shift of the ess during the initial 8 hr(hr)of cold exposure or depleted the microbiota composition and showed clustering of the samples intestinal microbiota using broad range antibiotics(Abx) admin- from the cold-exposed versus the room temperature(RT)groups istered in the drinking water. The higher fecal caloric content af- in both feces and cecum samples (Figures 1G, S2D, S2F, S3A, ter complete microbiota depletion was confirmed using bomb and S3B). Comparison of phylum level proportional abundance calorimetry(Figure S1G)and was consistent with previous re- in feces showed shifts in proportions(Figures 1H and S2C) ports(El Kaoutari et al., 2013), suggesting lower energy harvest especially in the ratio Firmicutes/Bacteroidetes where Firmi- from the food. Restricting the food access during acute cold cutes abundance(from 18.6% in RT up to 60.5% under cold exposure led to decreased body temperature(Figures 1A and increased over Bacteroidetes(from 72.6% in RT to 35.2% under 1B) compared to ad libitum-fed control mice and to a marked cold). The verrucomicrobia phylum was almost absent from both drop in the blood glucose and BW at cold(Figures S1H-S1J). feces and cecum after the cold exposure(from 12.5% for the Rt The decreased tolerance to cold and lowered blood glucose to 0.003% for the cold in cecum)(Figures 1H, S2C, and S2E) levels were also evident in the Abx-treated mice and the changes Interestingly, similar shifts, although less pronounced were relatively stable during short and long-term microbiota ciated with genetic and high fat diet-induced obesity (Turnbaugh depletion up to 4 weeks of treatment (Figures 1C-1E and S1K- et al., 2006). The shifts in phylum abundance correlated v S1R), despite the stable food intake and slightly increased water richness of the species present in them. Firmicutes phylum consumption (Figures S1S and S1T). These data suggest that the increased its richness in feces up to 78. 1% under cold exposure energy harvest during acute cold contributes to maintaining the (compared to 65% in RT) and Bacteroidetes decreased it to body temperature, and the intestinal microbiota is supporting 18.8%(compared to 29.7%in RT)(Figures 1I and 1J), without We observed that over time the overall fat loss was attenuated versity index(Figures S3C and S3D). From the 3. 86e n di- changing the overall bacterial diversity based on the Shan despite the stable food intake and EE(Figures S1A-S1F), sug- detected, using Welcht test done across the two groups ofsa US gesting compensatory mechanisms that enable increased ples using the abundance metrics, 252 OTUs(within 44 familie caloric harvest from the consumed food. To investigate whether were significantly different(p 0.05). Of the selected families, this prolonged cold exposure causes changes in the intestinal there were mixed responses in Firmicutes, Proteobacteria, microbiota, we collected feces at days 0, 11, and 31 and cecum and Bacteroidetes, however, those within Actinobacteria, Rectal body temperature(BT) of food restricted or ad libitum-fed C57BI6J mice after 4 and 8 hr(hr) of cold exposure(n 8 per group) 3) change in BT compared to initial as in(A) (C) Rectal BT after 3 hr of cold exposure of male mice treated or not treated with antibiotics (n =8 per group) (E Change in BT compared to initial as in(D) (F) Principal coordinates analysis(PCoA) based on weighted UniFrac analysis of OTUs. Each symbol represents a single sample of feces after 31 days of cold- exposed (n =8)or RT controls(n= 6 per group) Hierarchical clustering diagram using the average-neighbor(HC-AN) method comparing feces of 31 sed mice (n= 6). Associated heatmap shows the relative abundance of representative oTUs selected for p< 0.05, obtained with a Welch t test comparison groups and then grouped into families. One representative oTu with the greatest difference between the two group means from each family is se inclusion in the heatmap diagram OTUs are shown as: Phylum, Class, Order, Family, Genus, and Species. R, RT; C, cold-exposed and J)Richness represented as the pr of oTUs classified at the phylum rank. Feces. (J) Cecum. In (HJ)n=5+6(cecum) or 6 +8(feces). (K Heatmap tree comparing selected oTUs abundance from feces of T controls (n=6, inner rings) and 31 days cold-exposed mice(n=8, outer rings)and their phylogenic relationships. The OTUs representative of differentially abundant families are selected as described in(H) 1362cel163,1360-1374, December3,2015@2015 Elsevier Inc

homeostasis of the new host following microbiota transplantation remain poorly understood. Here, we show that the microbiota remodeling is an important contributor of the beige fat induction during cold and a key factor that promotes energy uptake by increasing the intestinal absorptive area, thus orchestrating the overall energy homeostasis during increased energy demand. RESULTS Cold Exposure Changes the Gut Microbiota Composition Short-term cold exposure for up to 10 days leads to increased EE relative to the energy uptake and suppresses BW and white fat mass gain (Figures S1A–S1F) (Wu et al., 2012, 2013). To investigate the importance of the acutely consumed food and caloric harvest during cold exposure, we restricted the food access during the initial 8 hr (hr) of cold exposure or depleted the intestinal microbiota using broad range antibiotics (Abx) administered in the drinking water. The higher fecal caloric content after complete microbiota depletion was confirmed using bomb calorimetry (Figure S1G) and was consistent with previous reports (El Kaoutari et al., 2013), suggesting lower energy harvest from the food. Restricting the food access during acute cold exposure led to decreased body temperature (Figures 1A and 1B) compared to ad libitum-fed control mice and to a marked drop in the blood glucose and BW at cold (Figures S1H–S1J). The decreased tolerance to cold and lowered blood glucose levels were also evident in the Abx-treated mice and the changes were relatively stable during short and long-term microbiota depletion up to 4 weeks of treatment (Figures 1C–1E and S1K– S1R), despite the stable food intake and slightly increased water consumption (Figures S1S and S1T). These data suggest that the energy harvest during acute cold contributes to maintaining the body temperature, and the intestinal microbiota is supporting this process. We observed that over time, the overall fat loss was attenuated despite the stable food intake and EE (Figures S1A–S1F), suggesting compensatory mechanisms that enable increased caloric harvest from the consumed food. To investigate whether this prolonged cold exposure causes changes in the intestinal microbiota, we collected feces at days 0, 11, and 31 and cecum post-mortem of cold-exposed mice and room temperature (RT) controls. Profiling of the microbiota composition by 16S rRNA gene sequencing, followed by principal coordinates analysis (PCoA) based on weighted UniFrac distance, showed major alterations of the microbiota content both in cecum and feces samples of cold-exposed animals (Figures 1F, S2A, and S2B). As expected, Firmicutes was the richest phylum in all samples (on average 69.10%) (Figures 1I and 1J). Bacteroidetes was the most abundant phylum (on average 63.50%) in all samples except the cold-exposed day 31 samples (Figures S2C–S2E). We observed differences in operational taxonomic units (OTUs) abundance at phylum level in Bacteroidetes, Firmicutes, Verrucomicrobia, Deferribacteres, Cyanobacteria, and Actinobacteria, and differences in OTU numbers at phylum-level in all the above plus Deferribacteres based on factor summary bar chart. Individual species, or family-based hierarchical clustering using the average-neighbor method, confirmed the major shift of the microbiota composition and showed clustering of the samples from the cold-exposed versus the room temperature (RT) groups in both feces and cecum samples (Figures 1G, S2D, S2F, S3A, and S3B). Comparison of phylum level proportional abundance in feces showed shifts in proportions (Figures 1H and S2C), especially in the ratio Firmicutes/Bacteroidetes where Firmicutes abundance (from 18.6% in RT up to 60.5% under cold) increased over Bacteroidetes (from 72.6% in RT to 35.2% under cold). The Verrucomicrobia phylum was almost absent from both feces and cecum after the cold exposure (from 12.5% for the RT to 0.003% for the cold in cecum) (Figures 1H, S2C, and S2E). Interestingly, similar shifts, although less pronounced, are associated with genetic and high fat diet-induced obesity (Turnbaugh et al., 2006). The shifts in phylum abundance correlated with the richness of the species present in them. Firmicutes phylum increased its richness in feces up to 78.1% under cold exposure (compared to 65% in RT) and Bacteroidetes decreased it to 18.8% (compared to 29.7% in RT) (Figures 1I and 1J), without changing the overall bacterial diversity based on the Shannon diversity index (Figures S3C and S3D). From the 3,864 OTUs detected, using Welch t test done across the two groups of samples using the abundance metrics, 252 OTUs (within 44 families) were significantly different (p < 0.05). Of the selected families, there were mixed responses in Firmicutes, Proteobacteria, and Bacteroidetes, however, those within Actinobacteria, Figure 1. Cold Exposure Changes the Gut Microbiota Composition (A) Rectal body temperature (BT) of food restricted or ad libitum-fed C57Bl6J mice after 4 and 8 hr (hr) of cold exposure (n = 8 per group). (B) Change in BT compared to initial as in (A). (C) Rectal BT after 3 hr of cold exposure of male mice treated or not treated with antibiotics (n = 8 per group). (D) Rectal BT after 4 hr and 24 hr of cold exposure in antibiotics-treated or control female mice (n = 6 per group). (E) Change in BT compared to initial as in (D). (F) Principal coordinates analysis (PCoA) based on weighted UniFrac analysis of OTUs. Each symbol represents a single sample of feces after 31 days of coldexposed (n = 8) or RT controls (n = 6 per group). (G) Hierarchical clustering diagram using the average-neighbor (HC-AN) method comparing feces of 31 days cold-exposed mice (n = 8) and their RT controls (n = 6). Associated heatmap shows the relative abundance of representative OTUs selected for p < 0.05, obtained with a Welch t test comparison of the two groups and then grouped into families. One representative OTU with the greatest difference between the two group means from each family is selected for inclusion in the heatmap diagram. OTUs are shown as: Phylum, Class, Order, Family, Genus, and Species. R, RT; C, cold-exposed. (H) Comparison of phylum-level proportional abundance of cecum and feces of up to 31 days cold-exposed or RT control mice. (I and J) Richness represented as the proportions of OTUs classified at the phylum rank. (I) Feces. (J) Cecum. In (H)–(J) n = 5 + 6 (cecum) or 6 + 8 (feces). (K) Heatmap tree comparing selected OTUs abundance from feces of RT controls (n = 6, inner rings) and 31 days cold-exposed mice (n = 8, outer rings) and their phylogenic relationships. The OTUs representative of differentially abundant families are selected as described in (H). See also Figures S1, S2, and S3. 1362 Cell 163, 1360–1374, December 3, 2015 ª2015 Elsevier Inc