1
Supplementary Information
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Supplementary Materials and Methods
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Denaturing gradient gel electrophoresis (DGGE) analysis of gut microbiota
4
A. PCR amplification and DGGE
5
DNA isolated from each faecal sample was used as template in the amplification of the V3
6
region of the 16S rRNA gene using the universal bacterial primers P2 (5’-
7
ATTACCGCGGCTGCTGG-3’) and P3 (5’-
8
CGCCCGCCGCGCGCGGCGGGCGGGGCGGGGGCACGGGGGGCCTACGGGAGGCA
9
GCAG-3’) and the hot-start touchdown protocol described by Muyzer et al(Muyzer et al.,
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1993) in a thermocycler PCR system (PCR Sprint, Thermo electron, Corp., UK). Each 25 μl
11
PCR reaction mixture contained 1.5 U of rTaq DNA polymerase (Takara, Dalian, China), 2.5
12
μl of the corresponding 10× buffer (Takara, Dalian, China), 0.2 mmol/L each
13
deoxynucleoside triphosphate (dNTP), 25 pmol of each primer, and 20 ng of total faecal
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DNA. After the initial amplification, a reconditioning PCR method was performed to
15
decrease heteroduplexes formation (Thompson et al., 2002). Parallel DGGE was performed
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using a Dcode System apparatus (Bio-Rad) in an 8% (w/v) acrylamide gel with a gradient
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from 27% to 52% and electrophoresis in 1× Tris-acetate-EDTA (TAE) buffer at the constant
18
voltage of 200 V and a temperature of 60oC for 240 minutes. After electrophoresis, the gels
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were stained with SYBR GreenⅠ (Amresco, Solon, Ohio) and visualized on a UVI gel
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documentation system (UVltec, Cambridge, United Kingdom).
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B. Sequence analysis of DGGE bands
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Important DGGE bands were excised from the original gel and incubated in 100 μl sterile
23
distilled water at 4°C overnight. A 1-μl aliquot of elution was used for PCR amplification of
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the DNA fragments from the excised gel with corresponding primers, P2 and P3. PCR
25
products was excised from a 1.0% agarose gel and purified with a DNA Gel Extraction Kit
26
(V-gene, Hangzhou, China). The products were ligated into the pGEM-T easy vector
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(Promega, Madison, WI) and transformed into competent E.coli DH5α cells (TIANGEN,
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China). Inserted DNA was amplified using corresponding primers and resolved by DGGE to
29
verify the position of the original band. Then three clones migrating to the same position of
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the original band were sequenced (Invitrogen, Shanghai, China).
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The sequences of excised DGGE bands were submitted to the RDP database (version 9.33)
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to determine their closest relatives with length greater than 1,200 nt. The sequences obtained
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are available in the GenBank database under accession numbers EU584214-EU584231.
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Terminal restriction fragment length polymorphism (T-RFLP) analysis of faecal
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samples
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A. 16S rRNA gene amplification and purification
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DNA isolated from each faecal sample was used as template in the amplification of the
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16S rRNA gene using the universal bacterial primers, 8F (5’-
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GAGAGTTTGATCCTGGCTCAG-3’), 5’ end labelled with D4, and 1492R (5’-
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GGC/TTACCTTGTTACGACTT-5’) (Hayashi et al., 2002). Each 25 μl PCR reaction
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mixture contained 1.5 U of rTaq DNA polymerase (Takara, Dalian, China), 2.5 μl of the
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corresponding 10× buffer (Takara, Dalian, China), 0.2 mmol/L each deoxynucleoside
43
triphosphate (dNTP), 25 pmol of each primer, and 10 ng of total faecal DNA. A 20 cycles
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PCR program (Eckburg et al., 2005) was performed with a thermocycler PCR system (PCR
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Sprint, Thermo electron, Corp., UK). Each 100 μl PCR product was digested by 1 U Mung
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bean nuclease (Promega, Madison, WI) to remove the single stranded extensions. Digestion
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products were purified with a DNA purification Kit (V-gene, Hangzhou, China), according to
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the manufacturer’s instruction.
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B. T-RFLP
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A 50-ng sample of 16S rRNA gene amplification product from each mouse sample was
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digested at 37°C for 3 h with 5 U of the following restriction endonucleases: AluⅠ, HaeⅢ,
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HhaⅠ, MspⅠ, or Csp6Ⅰ(Promega, Madison, WI). The efficiency of restriction digestion
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was confirmed by agarose gel electrophoresis, and the digested fragments were separated on
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a CEQTM 8000 genetic analysis system (Beckman Coulter). The sizes of the fluorescently
55
labelled fragments were determined by comparison with the internal size standard
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(GenomeLabTM DNA Size Standard 600 Kit, Beckman Coulter). Fluorescence intensity data
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were automatically collected and subsequently analyzed by the fragment analysis software
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provided with the CEQTM 8000 system. Relative peak areas of each TRF were determined
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by dividing the area of the peak of interest by the total area of peaks within the following
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threshold values: a lower threshold at 60 nt and an upper threshold at 640 nt. A threshold for
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relative peak area was applied at 3%, and only TRFs with higher relative abundances were
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included in the remaining analyses. The two peaks were identified as the same if the
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difference of the peak size was less than 1 nt. T-RFLP was repeated three times from each
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16S rRNA gene amplification.
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C. Statistical analysis of T-RFLP data
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In the matrix used for statistical analysis, the data of three replicates from each animal
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were as independent objects and the relative peak height of TRFs from every restriction
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endonuclease was as the variable. This matrix was used for PCA.
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variance (MANOVA) is a generalized form of analysis of variance (ANOVA) methods to
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cover cases where there is more than one (correlated) dependent variable and where the
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dependent variables cannot simply be combined, and the number of variables should less
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than the number of samples. Because the TFRs far outnumber our animals and PC1 to PC9
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from PCA, which accounts for 98% of total variations, PC1 to PC9 were used for
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Multivariate ANOVA test. The clusters are computed by applying the single linkage method
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to the matrix of Mahalanobis distances between group means. H returns a vector of handles
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to the lines in the figure. All the above methods were implemented in Matlab® (ver. 7.1,
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The MathWorks, Inc.).
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Pyrosequencing of 16S rRNA gene V3 region
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A. PCR amplification of 16S rRNA gene V3 region
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Multivariate analysis of
For faecal samples from each mouse, the extracted DNA was used as template in the
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amplification of the V3 region of 16S rRNA gene. The forward primer was 5’-
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NNNNNNNNCCTACGGGAGGCAGCAG-3’, and the reverse primer was5’-
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NNNNNNNNATTACCGCGGCTGCT-3’, where the underlined sequence is the universal
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bacterial primer P1 and P2. The NNNNNNNN is the unique eight base barcode used to
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distinguish PCR product from different samples. Reaction conditions were as follows: Each
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25 μl PCR reaction mixture contained 0.25 U of Platinum® Pfx DNA polymerase
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(Invitrogen, USA), 2.5 μl of the corresponding 10× Pfx amplification buffer (Invitrogen,
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USA), 0.5 mM of MgSO4 (Invitrogen, USA), 0.3 mmol/L each deoxynucleoside triphosphate
89
(dNTP), and 6.25 pmol of each primer, and 20 ng of total faecal DNA. PCR reactions were
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run in a thermocycler PCR system (PCR Sprint, Thermo electron, Corp., UK) using the
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following program: 3 minutes denaturing at 94°C followed by 20 cycles of 1 minute at 94°C
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(denaturing), 1 minute for annealing (1°C reduced for every 2 cycles from 65°C to 57°C
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followed by 1 cycle at 56°C and 1 cycle at 55°C), and 1 minute at 72°C (elongation), with a
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final extension at 72°C for 6 minutes. Three independent PCR reactions using different
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barcoded primers were performed for two animals from each group.
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B. Gel purification and pyrosequencing
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Each PCR product was isolated with the Gel/PCR DNA Fragments Extraction Kit
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(Geneaid, UKAS). 30 ng of each purified PCR product was mixed, and the mixture was
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purified from 1.2% agarose gel with the Gel/PCR DNA Fragments Extraction Kit (Geneaid,
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UKAS) and used as the DNA library for pyrosequencing using a GS20 platform (Roche), as
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described previously (Margulies et al., 2005). Based on several previous reports describing
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sources of errors in 454 sequencing runs (Margulies et al., 2005; Sogin et al., 2006;
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McKenna et al., 2008), standards were used for quality control, as follows: if a sequence (a)
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shows no mismatch to the barcode and 16S rRNA gene primer at sequencing end, (b) is more
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than 100 nt in length, (c) has no more than two undermined bases in the sequence read, and
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(d) finds more than 75% mach to a previously determined 16S rRNA gene sequence, then it
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will be regarded as usable. The unique sequences obtained in this study are available in the
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GenBank database under accession numbers FJ032696- FJ036862.
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C. Bioinformatic and Statistical analysis
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The unique V3 sequences of 16S rRNA gene from pyrosequencing were aligned using
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NAST multi-aligner with a minimum template length of 100 bases and a minimum percent
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identity of 75% (DeSantis et al., 2006). The resulting alignments were imported into the
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ARB (Ludwig et al., 2004) for construction of a neighbour-joining tree. The phylogenetic
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tree was then used for online UniFrac (http://bmf.colourado.edu/unifrac ) with abundance
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weighting (incorporating abundance data).
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A distance matrix of unique sequences from ARB was imported into DOTUR for
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phylotype binning (Schloss and Handelsman, 2005). The abundance information of each
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unique sequence was added to the OTU results from DOTUR, and measured for coverage
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(rarefaction analysis with software Past) and diversity (Shannon index with R software
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(http://www.r-project.org/)).
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OTUs were defined using a threshold of 97% identity, which was a criterion for species
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level delineation in previous studies (Huse et al., 2007). One sequence randomly selected
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from each OTU was BLAST searched against the RDP database (version 9.33) to identify the
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taxonomic group and inserted into pre-established phylogenetic trees of full length 16S
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rRNA gene sequences database from GreenGenes using ARB (hypervariable regions masked
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with the lanemaskPH filter) (Ludwig et al., 2004).
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Errors in pyrosequencing may occur at a rate of about 0.25%, suggesting that most of the
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200 nt sequences will contain either 0 or 1 error. Using the Poisson model, we would expect
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only 1.029e-6 of the reads to contain the six errors that would be required to form a new
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species-level at the 97% OTU identity. Thus, it is unlikely that a single OTU in analysis was
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generated through that mechanism.
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PLS-DA was used to test if two groups can be separated based on OTUs data. Martens’
uncertainty test was used to select significant OTUs which can discriminate the different
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treatment groups (different diets, host genotypes, or cages). One-way ANOVA was further
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performed to validate these differential variables. All statements of significance are at P<
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0.05. The correct prediction rate of the PLS-DA model was performed with leave-one-out
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CV.
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Quantitative Real-time PCR of Bifidobacterium spp.
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The plasmid containing the 16S rRNA gene of Bifidobacterium spp. was prepared with 3S
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Spin plasmid Miniprep Kit V3.1 (Shanghai Biocolour BioScience & Technology Company)
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and linearized with ScalⅠlinear. The plasmid was then diluted from 2.39E+9 to 2.39E+2
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(copies/μl) to make a standard curve. Real-time PCR amplification and detection were
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performed in the DNA Engine Opticon 2 system (MJ Research). The primers were the
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Bifidobacterium specific primers: Bif164-f (5’-GGGTGGTAATGCCGGATG-3’) and
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Bif662-r (5’-CCACCGTTACACCGGGAA-3’) (Satokari et al., 2001). The reaction mixture
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(25 μl) was composed of 1.5 U rTaq DNA polymerase (Takara, Dalian, China), 12.5μl of
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2×SYBR greenⅠmix (Shanghai Biocolour BioScience & Technology Company), 25 pmol of
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each primer, and 20 ng of total faecal DNA from each mouse or 1μl stander plasmid. The
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amplification program was as follows: one cycle of 94°C for 5 min, then 40 cycles of 94°C
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for 30 s, 62°C for 20 s, and 72°C for 40 s, and finally one cycle of 88°C for 10 s. The
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fluorescent product was detected at the last step of each cycle. Following amplification,
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melting temperature analysis of PCR products was performed to determine the specificity of
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the PCR. The melting curves were obtained by slow heating at 0.5°C/s increments from 70
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to 95°C, with continuous fluorescence collection. Each sample had three replicates of
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quantitative analysis. The data detected by the system was analyzed using Opticon Monitor
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(Version 1.1).
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Supplementary Results
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T-RFLP analysis of gut microbiota
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In the PCA based on T-RFLP data, the variables influenced PCs 1, 2, and 3 are shown in
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Figure S8.
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Pyrosequencing of 16S rRNA gene V3 region
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A total of 29,343 high quality sequences of pyrosequencing were first selected based on
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the following criteria: if a sequence (a) shows no mismatch to the barcode and 16S rRNA
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gene primer at sequencing end, (b) is more than 100 nt in length, (c) has no more than two
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undermined bases in the sequence read. All the sequences were aligned using NAST multi-
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aligner with a minimum template length of 100 bases and a minimum percent identity of
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75% (DeSantis et al., 2006). In all, 29 sequences had no neighbours with higher than 75%
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homology and were discarded. A total of 29,314 useable sequence reads were then obtained.
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There were 4,156 unique sequences in all the samples, 3,145 of which were detected only
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once. Because two animals from each treatment group had three replicates, we used 36
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different barcodes. All barcodes were well populated, with an average of 814 sequences per
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sample tested and only two samples had less than 500 reads (Table S 3).
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UniFrac provides a suite of tools for the comparison of microbial communities using
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phylogenetic information. The UniFrac analysis based on the unique sequences of all the
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four treatment groups revealed the significant impact of diet on gut microbiota (Fig.S2a), but
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the difference between mice having different genotypes was not obvious. These results
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confirmed that diets have a more significant influence on gut microbiota than genotypes.
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Hierarchical Clustering Analysis based on UniFrac analysis also indicated that the three
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replicates of the same animal were more similar to each other than to another animal
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(Fig.S2b). In other words, this 454 barcoded technology shows satisfactory reproducibility.
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In order to do phylotype binning and diversity estimation of our pyrosequencing data, the
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ARB distance matrix of sequence reads were imported to DOTUR. When sequences were
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condensed under 99% identity, 1,360 different operational taxonomic units (OTUs) were
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obtained. But the number of OTUs was reduced to 516 under 97% identity (Fig.S1a). The
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rarefaction analysis and Shannon Diversity Index were calculated for each of the 20 mice
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(Fig.S1b and 1c). For all the samples, the rarefaction curves did not reach a stable value,
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indicating that the actual numbers of OTUs in the samples are larger, echoing some recent
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reports based on pyrosequencing that the diversity of community of macaque gut or deep sea
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has been underestimated (McKenna et al., 2008)(Sogin et al., 2006). The curves of Shannon
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Diversity Index of all the samples had reached stable values. There was no significant
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difference of Shannon Diversity Index among the four groups.
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Analysis of the taxa present in the mice gut communities indicated that bacteria of
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Firmicutes and Bacteroidetes were dominant, which was followed by Actinobacteria and
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Proteobacteria. Phylum-wide changes associated with IGT/Obesity were not observed.
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More than 20 different families were found in the 20 mouse faecal samples, showing
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significant difference with the family level composition of gut bacteria in human (Ley et al.,
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2005). The relative abundance distribution of families showed individual-specific difference
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among the 20 mice (Fig.S5). The proportion of Erysipelotrichaceae was the highest in most
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mice.
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PLS-DA was used to find patterns out of this complex dataset. Using 97% identity to
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define OTUs, a PLS-DA scores plot with the first two components showed that animals with
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different diets, genotypes, or health phenotypes were separated into different classes
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(Fig.S3). The PLS-DA model of Apoa-Ⅰ-/- mice fed on different diets yielded a 99% correct
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classification rate in leave-one-out cross validation when 2 PLS components were used. The
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correct classification rate of wildtype mice fed different diets, animals with different
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genotypes fed HFD, and animals with different genotypes fed NC are as follows: 99% using
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1 PLS component, 80% using 2 PLS components, 90% using 2 PLS components. When the
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mice were divided into two groups based on the diet, the correct classification rate was 90%
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with 1 PLS component. When the mice were divided into two groups based on genotype, the
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correct classification rate was 75% with 2 PLS components. When the mice were divided
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into two groups based on health status, the correct classification rate was 95% with 2 PLS
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components.
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Sixty-five OTUs were selected using Martens’ uncertainty test key variables for the
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classifications. One random sequence from each of the key OTUs was inserted into the pre-
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established phylogenetic tree (Fig.S4). 21 OTUs (pink marked in the tree) increased in the
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mice group fed on HFD compared with their counterparts fed on NC, but 26 OTUs (blue)
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showed opposite behaviour. We also found 4 OTUs (yellow) with genotype-dependent
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reactions. For example, one phylotype, OTU 64 in Class Clostridia, was high in the Apoa-Ⅰ
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-/-
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S1). However, it disappeared completely in HFD groups regardless of genotype, confirming
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the results with DNA fingerprinting that high fat diet can diminish genotype-related
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differences. There was 1 OTU (purple) increased in the knockout mice, which may be only
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associated with genotype. There were 12 OTUs (green) reduced and 1 OTU (orange)
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abundant in mice with IGT. Four lineages were found in Class Erysipelotrichi, M1 (9 OTUs),
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M2 (6 OTUs), M3 (14 OTUs), M4 (1 OTU). M1 were abundant in healthy Wt/NC animals,
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but significantly reduced in the other three groups with IGT. M2 and M4 were predominant
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in HFD/obese groups and M3 had much higher population levels in NC/lean animals.
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/NC group but low in Wt/NC animals, showing a response to genotype difference (Table
When one sequence randomly selected from each OTU under 97% identity was BLAST
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searched against the RDP database (version 9.33) to identify the taxonomic group and
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inserted into pre-established phylogenetic trees of full length 16S rRNA gene sequences
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using ARB, more OTUs were found in the four lineages in Class Erysipelotrichi. The total
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OTUs in the four lineages M1-4 were 36, 30, 44, and 4, respectively. Those OTUs which
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were not selected as key variables for separating classes were mostly rare phylotypes.
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However, most rare phylotypes showed similar behaviour to the identified ones in the same
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lineage (Fig.S6).
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Real time PCR of Bifidobacterium
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Standard curve showed the linear relationship between the threshold cycles and the log
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quantity of the input standard plasmid (R2=0.999). Based on the standard curve, the average
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copy number of three replicates for each sample was calculated (Fig.S7). The
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Bifidobacterium spp. were present in all wildtype and most knockout mice on NC but
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disappeared in all HFD animals regardless of genotype.
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Supplementary References
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DeSantis, T.Z., Jr., Hugenholtz, P., Keller, K., Brodie, E.L., Larsen, N., Piceno, Y.M. et al.
(2006) NAST: a multiple sequence alignment server for comparative analysis of 16S rRNA
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Eckburg, P.B., Bik, E.M., Bernstein, C.N., Purdom, E., Dethlefsen, L., Sargent, M. et al.
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the collection of pyrosequencing reads was analyzed by condensing sequences at several
286
percent identity thresholds. The X-axis shows the percent identity, the Y-axis the number of
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OTUs detected. (b) Rarefaction analysis of sampling. Repeated samples of OTU subsets
288
were used to evaluate where further sampling would likely yield additional taxa, as indicated
289
by whether the curve has reached a plateau value. (c) Shannon Diversity Index curves to
290
estimate the diversity of taxa present in individual animals. Color code for each treatment
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group in this figures: green=Wt/NC; yellow=Wt/HFD; blue= Apoa-Ⅰ-/-/NC; red= Apoa-Ⅰ-/-
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/HFD.
Supplementary Figure Legends
Figure S1. Diversity of the mouse gut microbiota. (a) The numbers of OTUs present in
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Figure S2. Comparison of gut microbiota among groups of mice based on
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pyrosequencing data and Unifrac metrics. The phylogenetic tree of all unique sequences
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in four groups was used for UniFrac analysis. (a) The PCoA plot was generated using
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weighted UniFrac. (b) Hierarchical clustering analysis based on weighted UniFrac. Each
298
point represents an individual samples (two animals from each treatment group had three
299
replicates). Color code for each treatment group in this figures: green=Wt/NC;
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black=Wt/HFD; blue= Apoa-Ⅰ-/-/NC; red=Apoa-Ⅰ-/-/HFD.
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Figure S3. PLS-DA scores plots of first two components based on pyrosequencing OTU
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(97%) data. (a) A PLS-DA scores plot of Apoa-Ⅰ-/- mice given different diets. (b) A PLS-
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DA scores plot of wild-type mice given different diets. (c) A PLS-DA scores plot of Apoa-
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Ⅰ-/- and wild-type mice given HFD. (d) A PLS-DA scores plot of Apoa-Ⅰ-/- and wild-type
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mice given NC. (e) A PLS-DA scores plot of all the mice with the distinction of diet. (f) A
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PLS-DA scores plot of all the mice with the distinction of genotype. (g) A PLS-DA scores
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plot of all the mice with the distinction of IGT phenotype. Animal groups are color-coded as
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in Figure S2.
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Figure S4. Phylogeny of OTUs under 97% identity showing significant differences
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among four treatment groups of mice. 65 OTUs were selected using PLS-DA and
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Martens’ uncertainty test. One random sequence of each of these OTUs was inserted into the
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phylogenetic tree of full-length 16S rRNA gene sequences from the GreenGenes database.
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The sequences of important DGGE bands were also inserted into the tree. The color codes
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are as follows: pink=increased in high fat diet; blue=increased in normal chow; green,
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reduced in mice with IGT; orange=abundant in mice with IGT; yellow=genotype-dependent
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reaction to diet; purple=increased in Apoa-Ⅰ-/- mice.
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Figure S5. Summary of the bacterial taxa present in the gut community of each mouse.
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Each sample analyzed is indicated along the X-axis, the Y-axis indicates the relative
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abundance of each type (family) of bacteria present in that gut community. A key to the
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bacteria taxa is listed at the right.
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Figure S6. Comparison of abundance distribution OTUs and rare phylotypes in M1 -
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M4. (a) Abundance distribution of dominant OTUs in M1-M4, which were selected by as
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key variables for separating classes. (b) Abundance distribution of rare phylotypes in M1-
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M4, which were not selected as key variables for separating classes.
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Figure S7. Real-time PCR analysis of Bifidobacterium. Every sample had three
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replicates of RT-PCR, and the histogram shows the average copy numbers of
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Bifidobacterium spp. in every ng of faecal DNA from each mouse. Mean values ± SEM are
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shown.
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Figure S8. Coefficient of variables on PCs 1, 2, and 3 of T-RFLP data PCA analysis.
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The absolute value of coefficient of marked variable is more than 0.1. (a) Coefficient of
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variables on PC1. (b) Coefficient of variables on PC2. (c) Coefficient of variables on PC3.
Figure S1
Figure S2
Figure S3
Figure S4
Figure S5
Figure S6
Figure S7
Figure S8
Table S1 OTUs (97% identity) showing significant differences among the treatment groups of mice.
Closest Relatives (Identified sequences using RDP database)
Abundance distribution (%)
One-way ANOVA P value(s)
ApoaⅠ-/- High
Wild-type High
ApoaⅠ-/-
ApoaⅠ-/-
fat diet
fat diet
High fat diet
Normal chow
Representative
OTU
sequence
ApoaⅠ-/-
ApoaⅠ-/-
Wild-type
Wild-type
High fat
Normal
High fat
Normal
diet
chow
diet
chow
Healthy
High Fat Diet
Knockout
Similarity
ACC No.
Phylum
Class
Order
Family
VS.
VS.
VS.
VS.
ApoaⅠ-/-
Wild-type
Wild-type
Wild-type
Normal chow
Normal chow
High fat diet
Normal chow
VS.
VS.
VS.
(%)
Unhealthy
Normal chow
Wild-type
7
U000028382
EF096080
Proteobacteria
Deltaproteobacteria
Desulfovibrionales
Desulfovibrionaceae
100
2.03
2.13
4.68
0.75
/
0.0075
/
/
/
/
/
9
U000023613
EU504743
Bacteroidetes
Bacteroidetes
Bacteroidales
Porphyromonadaceae
99.4
0
3.94
0.81
1.25
0.0093
/
/
/
/
/
/
38
U000003735
EU009776
Bacteroidetes
Bacteroidetes
Bacteroidales
Porphyromonadaceae
94.3
0
0.53
0
1.16
/
0.032
/
/
/
0.0039
/
40
U000006061
EU009776
Bacteroidetes
Bacteroidetes
Bacteroidales
Porphyromonadaceae
93
0
0.39
0
1.11
/
0.045
/
/
/
0.0081
/
11
U000016351
EU504815
Bacteroidetes
Bacteroidetes
Bacteroidales
Porphyromonadaceae
99.4
1.93
1.1
3.77
0.67
/
0.000019
/
/
/
0.0073
/
180
U000025698
EF614639
Bacteroidetes
Bacteroidetes
Bacteroidales
98.1
0.016
0.024
0
0.1
/
/
/
/
0.0035
/
/
67
U000039702
AY850513
Bacteroidetes
Bacteroidetes
Bacteroidales
Porphyromonadaceae
89.1
0.46
0.44
0.014
0.1
/
/
/
/
/
/
0.0077
46
U000001832
EF406868
Bacteroidetes
Bacteroidetes
Bacteroidales
Porphyromonadaceae
100
0.37
0
1.99
0
/
0.039
/
/
/
0.0032
/
100
U000040596
EF097551
Bacteroidetes
Bacteroidetes
Bacteroidales
Porphyromonadaceae
95.6
0.016
0.14
0
0.17
/
0.013
/
/
/
/
/
81
U000016500
EF604763
Bacteroidetes
Bacteroidetes
Bacteroidales
Porphyromonadaceae
99.4
0.13
0.071
0.029
0.4
/
/
/
/
0.011
/
/
75
U000041621
DQ015203
Bacteroidetes
Bacteroidetes
Bacteroidales
Porphyromonadaceae
98.8
0.065
0.22
0.072
0.4
/
0.0077
/
/
0.0017
0.0025
/
62
U000031422
EF097211
Bacteroidetes
Bacteroidetes
Bacteroidales
Rikenellaceae
98.1
0.11
0.51
0.37
0.052
/
/
/
0.019
/
/
/
27
U000020286
AY174109
Actinobacteria
Actinobacteria
Bifidobacteriales
Bifidobacteriaceae
98.7
0
0
0
3.5
/
0.000011
/
/
/
/
/
15
U000024557
AY174109
Actinobacteria
Actinobacteria
Bifidobacteriales
Bifidobacteriaceae
98.1
0
1.88
0
3.5
/
0.0031
/
/
/
0.0016
/
8
U000031489
AY174109
Actinobacteria
Actinobacteria
Bifidobacteriales
Bifidobacteriaceae
100
0
2.39
0.014
6.3
/
0.00032
/
/
/
0.0064
/
183
U000003389
D86185
Actinobacteria
Actinobacteria
Bifidobacteriales
Bifidobacteriaceae
96.1
0
0.094
0.
0.077
/
/
/
/
/
0.041
/
36
U000001115
EU503611
Actinobacteria
Actinobacteria
Coriobacteriales
Coriobacteriaceae
100
0.39
0.38
0.97
0.83
/
/
/
/
/
/
0.03
52
U000014392
DQ071473
Actinobacteria
Actinobacteria
Coriobacteriales
Coriobacteriaceae
95.9
0.6
0
0
0.65
0.017
/
/
/
/
/
/
43
U000000324
DQ014810
Firmicutes
Clostridia
Clostridiales
Lachnospiraceae
99.3
0
1.57
0
0.052
/
/
/
0.017
/
0.023
/
91
U000033955
EF097536
Firmicutes
Clostridia
Clostridiales
Lachnospiraceae
97.8
0.42
0
0.1
0
/
0.013
/
/
/
0.011
/
161
U000033147
DQ015450
Firmicutes
Clostridia
Clostridiales
Lachnospiraceae
100
0
0.059
0
0.065
/
0.025
/
/
/
0.0073
/
108
U000005416
EU508080
Firmicutes
Clostridia
Clostridiales
Lachnospiraceae
92.8
0.16
0.012
0.27
0.013
/
/
/
/
/
0.014
/
64
U000009711
EU507738
Firmicutes
Clostridia
Clostridiales
Lachnospiraceae
99.3
0
0.12
0.79
0.065
/
0.0032
/
/
/
/
/
18
U000029595
EU506836
Firmicutes
Clostridia
Clostridiales
Lachnospiraceae
99.1
1.54
0.32
3.31
0.19
/
/
/
/
/
0.016
/
89
U000010964
EU508875
Firmicutes
Clostridia
Clostridiales
Ruminococcaceae
99.3
0.081
0
0.33
0
/
/
/
/
/
0.015
/
72
U000009642
EF603323
Firmicutes
Clostridia
Clostridiales
Ruminococcaceae
99.3
0.16
0.059
0.63
0.077
/
0.0015
0.007
/
/
0.0065
/
58
U000025890
EU509242
Firmicutes
Clostridia
Clostridiales
Ruminococcaceae
99.3
0.29
0.51
0.79
0.09
/
0.0067
/
/
/
/
/
59
U000000934
EU509809
Firmicutes
Clostridia
Clostridiales
Ruminococcaceae
99.3
0.33
0.15
0.6
0.052
/
0.0051
/
/
/
0.0055
/
39
U000017048
DQ815552
Firmicutes
Clostridia
Clostridiales
Ruminococcaceae
99
1.32
0.024
0.58
0
/
/
/
/
/
0.01
/
34
U000012845
EF603866
Firmicutes
Clostridia
Clostridiales
Lachnospiraceae
99.3
0.55
0.21
1.18
0.065
/
0.012
/
/
0.013
/
33
U000000486
DQ808568
Firmicutes
Clostridia
Clostridiales
Ruminococcaceae
99.3
1.93
0.024
0.89
0
/
/
/
/
/
0.0027
/
87
U000002211
DQ325814
Firmicutes
Clostridia
Clostridiales
Lachnospiraceae
100
0.46
0.047
0.37
0.052
/
/
/
/
/
0.025
/
74
U000008559
EF096608
Firmicutes
Clostridia
Clostridiales
Lachnospiraceae
99.3
0.39
0.21
0.95
0.065
/
/
/
/
/
0.015
/
24
U000030860
EU507383
Firmicutes
Clostridia
Clostridiales
Lachnospiraceae
99.4
1.2
0.46
1.05
0.15
/
0.000089
/
/
0.00069
0.00022
/
28
U000030555
AY328550
Firmicutes
Bacilli
Lactobacillales
Streptococcaceae
100
1.19
0.54
1.11
0.14
/
0.012
/
/
0.013
0.0018
/
77
U000037248
EU510844
Firmicutes
Erysipelotrichi
Erysipelotrichales
Erysipelotrichaceae
98.8
0.081
0.035
0
0.86
/
0.0022
/
0.0029
0.00016
/
/
145
U000027359
EU508960
Firmicutes
Erysipelotrichi
Erysipelotrichales
Erysipelotrichaceae
96.4
0
0
0
0.14
/
0.033
/
0.033
0.00017
/
/
357
U000029900
EU505653
Firmicutes
Erysipelotrichi
Erysipelotrichales
Erysipelotrichaceae
94.6
0
0
0
0.065
/
/
/
/
0.0013
/
/
88
U000018234
EU507232
Firmicutes
Erysipelotrichi
Erysipelotrichales
Erysipelotrichaceae
99.4
0.033
0.012
0.014
0.86
/
0.00026
/
0.00015
0.00016
/
/
212
U000034857
EU511304
Firmicutes
99.4
0
0.012
0
0.1
/
0.048
/
/
0.0011
/
/
141
U000002839
EU507232
Firmicutes
Erysipelotrichi
Erysipelotrichales
Erysipelotrichaceae
98.8
0.016
0
0.014
0.3
/
0.032
/
0.029
0.0017
/
/
6
U000034579
EU505377
Firmicutes
Erysipelotrichi
Erysipelotrichales
Erysipelotrichaceae
99.4
0.88
0.24
0.37
12.5
/
0.00049
/
0.00035
0.00016
/
/
56
U000006185
EU508960
Firmicutes
Erysipelotrichi
Erysipelotrichales
Erysipelotrichaceae
96.9
0.13
0.035
0.043
1.85
/
0.0024
/
0.0015
0.00016
/
/
217
U000037797
EU511394
Firmicutes
Erysipelotrichi
Erysipelotrichales
Erysipelotrichaceae
99.4
0
0
0
0.34
/
0.0021
/
0.0021
0.00016
/
/
2
U000035271
EU505669
Firmicutes
Erysipelotrichi
Erysipelotrichales
Erysipelotrichaceae
99.4
24.3
0.083
3.86
0.93
0.0021
0.046
0.037
/
/
0.00082
/
131
U000008904
EU503568
Firmicutes
Erysipelotrichi
Erysipelotrichales
Erysipelotrichaceae
99.4
0.88
0.035
0.14
0.013
0.02
/
/
/
/
0.0082
/
26
U000008160
EU505483
Firmicutes
Erysipelotrichi
Erysipelotrichales
Erysipelotrichaceae
99.4
2.8
0.024
0.32
0.026
0.014
0.045
/
/
/
0.0069
/
5
U000010299
EU503724
Firmicutes
Erysipelotrichi
Erysipelotrichales
Erysipelotrichaceae
98.8
13.9
0.17
2.87
0.3
0.0021
/
/
/
/
0.00046
/
359
U000022068
EU503645
Firmicutes
Erysipelotrichi
Erysipelotrichales
Erysipelotrichaceae
99.4
0.098
0
0.014
0
/
/
/
/
/
0.029
/
101
U000021437
EU503645
Firmicutes
Erysipelotrichi
Erysipelotrichales
Erysipelotrichaceae
99.4
0.37
0
0.014
0.026
0.0016
/
0.0026
/
/
0.019
/
86
U000035671
EF603858
Firmicutes
Erysipelotrichi
Erysipelotrichales
Erysipelotrichaceae
98.8
0.016
0.31
0
0.46
/
0.00049
/
/
/
0.0044
/
127
U000037422
EF603858
Firmicutes
Erysipelotrichi
Erysipelotrichales
Erysipelotrichaceae
98.2
0.016
0.059
0
0.15
/
0.0029
/
/
/
0.034
/
21
U000024281
EF603858
Firmicutes
Erysipelotrichi
Erysipelotrichales
Erysipelotrichaceae
97.6
0.098
1.88
0.029
1.85
/
0.00036
/
/
/
0.0014
/
227
U000026824
EF603858
Firmicutes
Erysipelotrichi
Erysipelotrichales
Erysipelotrichaceae
100
0
0.15
0
0.077
/
/
/
/
/
0.027
/
134
U000001902
EF603858
Firmicutes
Erysipelotrichi
Erysipelotrichales
Erysipelotrichaceae
99.4
0
0.2
0
0.18
/
/
/
/
/
0.012
/
208
U000035866
EU511581
Firmicutes
Erysipelotrichi
Erysipelotrichales
Erysipelotrichaceae
93.9
0
0
0
0.065
/
0.013
/
/
/
/
/
214
U000035767
EF603858
Firmicutes
Erysipelotrichi
Erysipelotrichales
Erysipelotrichaceae
99.4
0
0.11
0
0.12
/
/
/
/
/
0.0033
/
185
U000036828
EF603858
Firmicutes
Erysipelotrichi
Erysipelotrichales
Erysipelotrichaceae
98.2
0
0.083
0
0.1
/
/
/
/
/
0.0097
/
102
U000038832
EF603858
Firmicutes
Erysipelotrichi
Erysipelotrichales
Erysipelotrichaceae
97.5
0
0.19
0
0.24
/
0.0025
/
/
/
0.00037
/
1
U000029463
EF603858
Firmicutes
Erysipelotrichi
Erysipelotrichales
Erysipelotrichaceae
98.8
0.91
29.6
0.37
30.2
0.023
0.000022
/
/
/
0.00019
/
116
U000038624
EF603858
Firmicutes
Erysipelotrichi
Erysipelotrichales
Erysipelotrichaceae
98.8
0
0.4
0
0.34
/
0.0049
/
/
/
0.019
/
160
U000029891
EF603858
Firmicutes
Erysipelotrichi
Erysipelotrichales
Erysipelotrichaceae
96.2
0
0.19
0
0.28
/
0.002
/
/
/
0.00037
/
219
U000026363
EF603858
Firmicutes
Erysipelotrichi
Erysipelotrichales
Erysipelotrichaceae
99
0.016
0.059
0
0.026
/
/
/
/
/
0.013
/
201
U000034887
EF603858
Firmicutes
Erysipelotrichi
Erysipelotrichales
Erysipelotrichaceae
96.9
0
0.083
0
0.18
/
0.011
/
/
/
0.0015
/
35
U000018452
EU507348
Firmicutes
Erysipelotrichi
Erysipelotrichales
Erysipelotrichaceae
99.4
1.5
0.024
0.66
0.13
/
/
/
/
/
0.00096
/
22
Table S2 Sequence analysis of the significant different V3 DGGE bands between groups.
Band
No.
Closest molecular relatives and isolates identified from RDP database
Organism (Similarity)
Phylum
Class
Order
Family
Clostridium cocleatum
Firmicutes
Erysipelotrichi Erysipelotrichales
Erysipelotrichaceae
Firmicutes
Erysipelotrichi Erysipelotrichales
Erysipelotrichaceae
Firmicutes
Erysipelotrichi Erysipelotrichales
Erysipelotrichaceae
Firmicutes
Erysipelotrichi Erysipelotrichales
Erysipelotrichaceae
Firmicutes
Erysipelotrichi Erysipelotrichales
Erysipelotrichaceae
Firmicutes
Erysipelotrichi Erysipelotrichales
Erysipelotrichaceae
Firmicutes
Erysipelotrichi Erysipelotrichales
Erysipelotrichaceae
Firmicutes
Erysipelotrichi Erysipelotrichales
Erysipelotrichaceae
Firmicutes
Erysipelotrichi Erysipelotrichales
Erysipelotrichaceae
Firmicutes
Erysipelotrichi Erysipelotrichales
Erysipelotrichaceae
AF028350 (100%)
1
Clostridium cocleatum(T)
Y18188 (99.5%)
Uncultured bacterium
EU503645 (100%)
2
Allobaculum stercoricanis (T)
AJ417075 (85.6%)
Uncultured bacterium
EU503646 (100%)
3
Allobaculum stercoricanis (T)
AJ417075 (85.6%)
Uncultured bacterium
EU503571 (100%)
4
Allobaculum stercoricanis (T)
AJ417075 (85.6%)
Uncultured bacterium
6a
EF603858 (99.5%)
Allobaculum stercoricanis (T)
23
AJ417075 (92.3%)
Uncultured bacterium
Bacteroidetes
Bacteroidetes
Bacteroidales
Porphyromonadaceae
Bacteroidetes
Flavobacteria
Flavobacteriales
Flavobacteriaceae
Actinobacteria Actinobacteria
Bifidobacteriales
Bifidobacteriaceae
Actinobacteria Actinobacteria
Bifidobacteriales
Bifidobacteriaceae
Actinobacteria Actinobacteria
Bifidobacteriales
Bifidobacteriaceae
Actinobacteria Actinobacteria
Bifidobacteriales
Bifidobacteriaceae
Firmicutes
Erysipelotrichi Erysipelotrichales
Erysipelotrichaceae
Firmicutes
Erysipelotrichi Erysipelotrichales
Erysipelotrichaceae
EU504743 (99.5%)
6b
cf.Bergeyella sp.CCUG 46293 (T)
AJ575430 (81.5%)
Bifidobacterium pseudolongum subsp. pseudolongum
AY174109 (98.9%)
10
Bifidobacterium animalis subsp. animalis (T)
AY722379 (98.9%)
Bifidobacterium animalis subsp. animalis
D86185 (97.9%)
11
Bifidobacterium animalis subsp. animalis (T)
AY722379 (97.8%)
Uncultured bacterium
EU507135 (100%)
12
Allobaculum stercoricanis (T)
AJ417075 (87.6%)
24
Table S3
Pyrosequencing reads of all samples.
Total Unique
Group
NO.
Total Unique
Group
NO.
reads sequence
1
reads sequence
577
165
1
510
119
2a 595
171
2
335
93
2b 524
154
3a 640
204
2c 469
152
3b 1419
315
3c 607
178
ApoaⅠ-/-
Wildtype
3
886
242
High fat diet
High fat diet
4
629
160
4
861
245
5a 706
174
5a 1167
341
5b 879
174
5b 762
239
5c 887
182
5c 642
221
1a 944
224
1a 711
229
1b 1080
286
1b 842
248
1c 921
249
1c 779
213
2 1006
278
2
864
280
3
207
3
925
237
ApoaⅠ-/-
Wildtype
750
Normal chow
Normal chow
4a 927
227
4
964
270
4b 865
223
5a 922
220
4c 978
256
5b 947
218
5
255
5c 796
198
998