Development and application of the human intestinal tract chip, a phylogenetic microarray: analysis of universally conserved phylotypes in the abundant microbiota of young and elderly adults

Mirjana Rajilić-Stojanović, Hans G H J Heilig, Douwe Molenaar, Kajsa Kajander, Anu Surakka, Hauke Smidt, Willem M de Vos, Mirjana Rajilić-Stojanović, Hans G H J Heilig, Douwe Molenaar, Kajsa Kajander, Anu Surakka, Hauke Smidt, Willem M de Vos

Abstract

In this paper we present the in silico assessment of the diversity of variable regions of the small subunit ribosomal RNA (SSU rRNA) gene based on an ecosystem-specific curated database, describe a probe design procedure based on two hypervariable regions with minimal redundancy and test the potential of such probe design strategy for the design of a flexible microarray platform. This resulted in the development and application of a phylogenetic microarray for studying the human gastrointestinal microbiota--referred as the human intestinal tract chip (HITChip). Over 4800 dedicated tiling oligonucleotide probes were designed based on two hypervariable regions of the SSU rRNA gene of 1140 unique microbial phylotypes (< 98% identity) following analysis of over 16,000 human intestinal SSU rRNA sequences. These HITChip probes were hybridized to a diverse set of human intestinal samples and SSU rRNA clones to validate its fingerprinting and quantification potential. Excellent reproducibility (median Pearson's correlation of 0.99) was obtained following hybridization with T7 polymerase transcripts generated in vitro from SSU rRNA gene amplicons. A linear dose-response was observed with artificial mixtures of 40 different representative amplicons with relative abundances as low as 0.1% of total microbiota. Analysis of three consecutively collected faecal samples from ten individuals (five young and five elderly adults) revealed temporal dynamics and confirmed that the adult intestinal microbiota is an individual-specific and relatively stable ecosystem. Further analysis of the stable part allowed for the identification of a universal microbiota core at the approximate genus level (90% sequence similarity). This core consists of members of Actinobacteria, Bacteroidetes and Firmicutes. Used as a phylogenetic fingerprinting tool with the possibility for relative quantification, the HITChip has the potential to bridge the gaps in our knowledge in the quantitative and qualitative description of the human gastrointestinal microbiota composition.

Figures

Fig. 2
Fig. 2
Correlation between relative abundance of ten phylogenetic groups assessed as average of the group-specific HITChip hybridization signals (empty columns) and FISH quantification (filled columns) based on the analysis of faecal microbiota of five subjects. Error bars indicate standard deviations.
Fig. 1
Fig. 1
Correlation of results obtained by the Bifidobacterium-specific FISH quantification and sum of the Bifidobacterium-specific HITChip hybridization signals for 60 faecal samples. Faecal samples obtained from 20 individuals in three time points were analysed, of which four samples that did not reach detection limit with the FISH are not plotted on the graph.
Fig. 3
Fig. 3
Clustering of the HITChip phylogenetic fingerprints of the human gastrointestinal microbiota of three faecal samples of ten subjects collected during period of at least two months. Samples are encoded by YA1–YA5 for younger adults, and by EA1–EA5 for elderly adults, while 1, 2 or 3 subsequent to slash sign indicate sample collection sequence. The highest phylogenetic level of specificity of probes (level 1) is depicted on the right panel of the figure.
Fig. 4
Fig. 4
Similarity of the intestinal microbiota profiles for ten individuals calculated for 1 (grey bars) and two month (open bars) span. Results for total microbiota and six level 1 groups of the microbiota (phyla Actinobacteria, Bacteroidetes and Proteobacteria, and three groups within the Firmicutes phylum) are presented as box whisker plot. The box extends from the first quartile until the third quartile, with a line at the median, while whiskers are indicating minimal and maximal observation in the data set.
Fig. 5
Fig. 5
Venn diagram showing the distribution of the HITChip probes that showed significant hybridization signal when analysing five younger adults (A), five elderly adults (B) and between the core of younger and elderly adults (C). Only the core probes (those that were corresponding in all three analysed samples per subject) were taken into consideration for this analysis. For subject codes see Fig. 3. The image was generated using AutoFocus software (Aduna B.V., the Netherlands).

References

    1. Acinas SG, Sarma-Rupavtarm R, Klepac-Ceraj V, Polz MF. PCR-induced sequence artifacts and bias: insights from comparison of two 16S rRNA clone libraries constructed from the same sample. Appl Environ Microbiol. 2005;71:8966–8969.
    1. Altschul SF, Gish W, Miller W, Meyers EW, Lipman DJ. Basic Local Alignment Search Tool. J Mol Biol. 1990;215:403–410.
    1. Andersson AF, Lindberg M, Jakobsson H, Backhed F, Nyren P, Engstrand L. Comparative analysis of human gut microbiota by barcoded pyrosequencing. PLoS ONE. 2008;3:e2836.
    1. Bäckhed F, Ley RE, Sonnenburg JL, Peterson DA, Gordon JI. Host-bacterial mutualism in the human intestine. Science. 2005;307:1915–.
    1. Bauer DF. Constructing confidence sets using rank statistics. J Am Stat Assoc. 1972;67:687–690.
    1. Ben-Amor K, Heilig HG, Smidt H, Vaughan EE, Abee T, de Vos WM. Genetic diversity of viable, injured, and dead fecal bacteria assessed by fluorescence-activated cell sorting and 16S rRNA gene analysis. Appl Environ Microbiol. 2005;71:4679–4689.
    1. Bertilsson S, Cavanaugh CM, Polz MF. Sequencing-independent method to generate oligonucleotide probes targeting a variable region in bacterial 16S rRNA by PCR with deatachable primers. Appl Environ Microbiol. 2002;68:6077–6086.
    1. Blanchard AP, Kaiser RJ, Hood LE. High-density oligonucleotide arrays. Biosens Bioelectron. 1996;11:687–690.
    1. Bodrossy L, Sessitsch A. Oligonucleotide microarrays in microbial diagnostics. Curr Opin Microbiol. 2004;7:245–254.
    1. Bodrossy L, Stralis-Pavese N, Murrell JC, Radajewski S, Weilharter A, Sessitsch A. Development and validation of a diagnostic microbial microarray for methanotrophs. Environ Microbiol. 2003;5:566–582.
    1. Bolstad BM, Irizarry RA, Astrand M, Speed TP. A comparison of normalization methods for high density oligonucleotide array data based on variance and bias. Bioinformatics. 2003;19:185–193.
    1. Bonnet R, Suau A, Doré J, Gibson GR, Collins MD. Differences in rDNA libraries of faecal bacteria derived from 10- and 25-cycle PCRs. Int J Syst Evol Microbiol. 2002;52:757–763.
    1. ter Braak CJF, Šmilauer P. canoco Reference Manual and CanoDraw for Windows User's Guide: Software for Canonical Community Ordination. Ithaca, NY, USA: Microcomputer Power.; 2002. version 4.5.
    1. Button DK, Robertson BR. Determination of DNA content of aquatic bacteria by flow cytometry. Appl Environ Microbiol. 2001;67:1636–1645.
    1. Chee M, Yang R, Hubbell E, Berno A, Huang XC, Stern D, et al. Accessing genetic information with high-density DNA arrays. Science. 1996;274:610–614.
    1. Cleveland WS, Grosse E, Shyu WM. Local regression models. In: Chambers JM, Hastie TJ, editors. Statistical Models in S. Cole, USA: Wadsworth & Brooks/Cole Computer Science Series; 1992. pp. 309–376.
    1. Collins M, Lawson P, Willems A, Cordoba J, Fernandez-Garayzabal J, Garcia P, et al. The phylogeny of the genus Clostridium: proposal of five new genera and eleven new species combinations. Int J Syst Bacteriol. 1994;44:812–826.
    1. DeSantis TZ, Brodie EL, Moberg JP, Zubieta IX, Piceno YM, Andersen GL. High-density universal 16S rRNA microarray analysis reveals broader diversity than typical clone library when sampling the environment. Microb Ecol. 2007;53:371–383.
    1. Dethlefsen L, Eckburg PB, Bik EM, Relman DA. Assembly of the human intestinal microbiota. Trends Ecol Evol. 2006;21:517–523.
    1. Dixon WJ. Analysis of extreme values. Ann Math Stat. 1950;21:488–506.
    1. Eckburg PB, Bik EM, Bernstein CN, Purdom E, Dethlefsen L, Sargent M, et al. Diversity of the human intestinal microbial flora. Science. 2005;308:1635–1638.
    1. Emrich SJ, Lowe M, Delcher AL. PROBEmer: a web-based software tool for selecting optimal DNA oligos. Nucleic Acids Res. 2003;31:3746–3750.
    1. Favier CF, Vaughan EE, de Vos WM, Akkermans ADL. Molecular monitoring of succession of bacterial communities in human neonates. Appl Environ Microbiol. 2002;68:219–226.
    1. Fogarty LR, Voytek MA. Comparison of Bacteroides-Prevotella 16S rRNA genetic markers for fecal samples from different animal species. Appl Environ Microbiol. 2005;71:5999–6007.
    1. Gentry TJ, Wickham GS, Schadt CW, He Z, Zhou J. Microarray applications in microbial ecology research. Microb Ecol. 2006;52:159–175.
    1. Gill SR, Pop M, Deboy RT, Eckburg PB, Turnbaugh PJ, Samuel BS, et al. Metagenomic analysis of the human distal gut microbiome. Science. 2006;312:1355–1359.
    1. Guschin DY, Mobarry BK, Proudnikov D, Stahl DA, Rittmann BE, Mirzabekov AD. Oligonucleotide microchips as genosensors for determinative and environmental studies in microbiology. Appl Environ Microbiol. 1997;63:2397–2402.
    1. Heuer H, Hartung K, Wieland G, Kramer I, Smalla K. Polynuclotide probes that target a hypervariable region of 16S rRNA genes to identify bacterial isolates corresponding to bands of community fingerprints. Appl Environ Microbiol. 1999;65:1045–1049.
    1. Horz HP, Vianna ME, Gomes BPFA, Conrads G. Evaluation of universal probes and primer sets for assessing total bacterial load in clinical samples: general implications and practical use in endodontic antimicrobial therapy. J Clin Microbiol. 2005;43:5332–5337.
    1. Hugenholtz P, Pitulle C, Hershberger KL, Pace NR. Novel division level bacterial diversity in a Yellowstone hot spring. J Bacteriol. 1998;180:366–376.
    1. Klappenbach JA, Saxman PR, Cole JR, Schmidt TM. rrndb: the ribosomal RNA operon copy number database. Nucleic Acids Res. 2001;29:181–184.
    1. Kurokawa K, Itoh T, Kuwahara T, Oshima K, Toh H, Toyoda A, et al. Comparative metagenomics revealed commonly enriched gene sets in human gut microbiomes. DNA Res. 2007;14:169–181.
    1. Lane DJ. 16S/23S rRNA sequencing. In: Stackebrandt E, Goodfellow M, editors. Nucleic Acid Techniques in Bacterial Systematics. Chichester, UK: J. Wiley & Sons; 1991. pp. 115–175.
    1. Larkin JE, Frank BC, Gavras H, Sultana R, Quackenbush J. Independence and reproducibility across microarray platforms. Nat Methods. 2005;2:337–344.
    1. Lay C, Rigottier-Gois L, Holmstrom K, Rajilic M, Vaughan EE, de Vos WM, et al. Colonic microbiota signatures across five Northern European countries. Appl Environ Microbiol. 2005;71:4153–4155.
    1. Leitch EC, Walker AW, Duncan SH, Holtrop G, Flint HJ. Selective colonization of insoluble substrates by human faecal bacteria. Environ Microbiol. 2007;9:667–679.
    1. Lepš J, Šmilauer P. Multivariate Analysis of Ecological Data Using CANOCO. Cambridge, UK: Cambridge University Press; 2003.
    1. Ley RE, Turnbaugh PJ, Klein S, Gordon JI. Microbial ecology: human gut microbes associated with obesity. Nature. 2006;444:1022–1023.
    1. Li M, Wang B, Zhang M, Rantalainen M, Wang S, Zhou H, et al. Symbiotic gut microbes modulate human metabolic phenotypes. Proc Natl Acad Sci U S A. 2008;105:2117–2122.
    1. Li X, He Z, Zhou J. Selection of optimal oligonucleotide probes for microarrays using multiple criteria, global alignment and parameter estimation. Nucleic Acids Res. 2005;33:6114–6123.
    1. Loy A, Lehner A, Lee N, Adamczyk J, Meier H, Ernst J, et al. Oligonucleotide microarray for 16S rRNA gene-based detection of all recognized lineages of sulfate-reducing prokaryotes in the environment. Appl Environ Microbiol. 2002;68:5064–5081.
    1. Ludwig W, Strunk O, Westram R, Richter L, Meier H, Yadhukumar, et al. ARB: a software environment for sequence data. Nucleic Acids Res. 2004;32:1363–1371.
    1. McCartney AL, Wenzhi W, Tannock GW. Molecular analysis of the composition of the bifidobacterial and lactobacillus microflora of humans. Appl Environ Microbiol. 1996;62:4608–4613.
    1. Matsuki T, Watanabe K, Fujimoto J, Miyamoto Y, Takada T, Matsumoto K, et al. Development of 16S rRNA-gene-targeted group-specific primers for the detection and identification of predominant bacteria in human feces. Appl Environ Microbiol. 2002;68:5445–5451.
    1. Matsuki T, Watanabe K, Fujimoto J, Takada T, Tanaka R. Use of 16S rRNA gene-targeted group-specific primers for real-time PCR analysis of predominant bacteria in human feces. Appl Environ Microbiol. 2004;70:7220–7228.
    1. Mitsuoka T. Intestinal flora and aging. Nutr Rev. 1992;50:438–446.
    1. Mueller S, Saunier K, Hanisch C, Norin E, Alm L, Midtvedt T, et al. Differences in fecal microbiota in different European study populations in relation to age, gender, and country: a cross-sectional study. Appl Environ Microbiol. 2006;72:1027–1033.
    1. Myllyluoma E, Veijola L, Ahlroos T, Tynkkynen S, Kankuri E, Vapaatalo H, et al. Probiotic supplementation improves tolerance to Helicobacter pylori eradication therapy – a placebo-controlled, double-blind randomized pilot study. Aliment Pharmacol Ther. 2005;21:1263–1272.
    1. Nicholson JK, Holmes E, Wilson ID. Gut microorganisms, mammalian metabolism and personalized health care. Nat Rev Microbiol. 2005;3:431–438.
    1. Nübel U, Engelen B, Felske A, Snaidr J, Wieshuber A, Amann RI, et al. Sequence heterogeneities of genes encoding 16S rRNAs in Paenibacillus polymyxa detected by temperature gradient gel electrophoresis. J Bacteriol. 1996;178:5636–5643.
    1. Palmer C, Bik EM, Eisen MB, Eckburg PB, Sana TR, Wolber PK, et al. Rapid quantitative profiling of complex microbial populations. Nucleic Acids Res. 2006;34:e5.
    1. Palmer C, Bik EM, Digiulio DB, Relman DA, Brown PO. Development of the human infant intestinal microbiota. PLoS Biol. 2007;5:e177.
    1. Panjkovich A, Melo F. Comparison of different melting temperature calculation methods for short DNA sequences. Bioinformatics. 2004;21:711–722.
    1. Panjkovich A, Melo F. Comparison of different melting temperature calculation methods for short DNA sequences. Bioinformatics. 2005;21:711–712.
    1. Possemiers S, Verthé K, Uyttendaele S, Verstraete W. PCR-DGGE-based quantification of stability of the microbial community in a simulator of the human intestinal microbial ecosystem. FEMS Microbiol Ecol. 2004;49:495–507.
    1. Pozhitkov A, Noble PA, Domazet-Loso T, Nolte AW, Sonnenberg R, Staehler P, et al. Tests of rRNA hybridization to microarrays suggest that hybridization characteristics of oligonucleotide probes for species discrimination cannot be predicted. Nucleic Acids Res. 2006;34:e66.
    1. Rajilić-Stojanović M, Smidt H, de Vos WM. Diversity of the human gastrointestinal tract microbiota revisited. Environ Microbiol. 2007;9:2125–2136.
    1. Roest KC. Microbial community analysis in sludge of anaerobic wastewater treatment systems. In: de Vos WM, Stams AJM, editors. Laboratory of Microbiology. Wageningen, the Netherlands: Wageningen University; 2007. p. 174. p.
    1. Royston P. An extension of Shapiro and Wilk's W test for normality to large samples. Appl Stat. 1982;31:115–124.
    1. Sacchi CT, Alber D, Dull P, Mothershed EA, Whitney AM, Barnett GA, et al. High level of sequence diversity in the 16S rRNA genes of Haemophilus influenzae isolates is useful for molecular subtyping. J Clin Microbiol. 2005;43:3734–3742.
    1. Sambrook J, Fritsch EF, Maniatis T. Calculating melting temperatures for perfectly matched hybrids between oligonucleotides and their target sequences. In: Sambrook J, Fritsch EF, Maniatis T, editors. Molecular Cloning – A Laboratory Manual. Cold Spring Habour, NY, USA: Cold Spring Habour Laboratory Press; 1989a. p. 11.46.. p.
    1. Sambrook J, Fritsch EF, Maniatis T. Preparation of reagents and buffers used in molecular cloning. In: Sambrook J, Fritsch EF, Maniatis T, editors. Molecular Cloning – A Laboratory Manual. Cold Spring Habour, NY, USA: Cold Spring Habour Habour Laboratory Press; 1989b. p. B.13.. p.
    1. SantaLucia J., Jr. A unified view of polymer, dumbbell, and oligonucleotide DNA nearest-neighbor thermodynamics. Proc Natl Acad Sci USA. 1998;95:1460–1465.
    1. Scanlan PD, Shanahan F, Clune Y, Collins JK, O'Sullivan GC, O'Riordan M, et al. Culture-independent analysis of the gut microbiota in colorectal cancer and polyposis. Environ Microbiol. 2008;10:789–798.
    1. Schloss PD, Handelsman J. Status of the microbial census. Microbiol Mol Biol Rev. 2004;68:686–691.
    1. Shen J, Zhang B, Wei G, Pang X, Wei H, Li M, et al. Molecular profiling of the clostridium leptum subgroup in human fecal microflora by PCR-denaturing gradient gel electrophoresis and clone library analysis. Appl Environ Microbiol. 2006;72:5232–5238.
    1. Suau A, Bonnet R, Sutren M, Godon J-J, Gibson GR, Collins MD, Doré J. Direct analysis of genes encoding 16S rRNA from complex communities reveals many novel molecular species within the human gut. Appl Environ Microbiol. 1999;65:4799–4807.
    1. Surakka A, Kajander K, Rajilić-Stojanović M, Karjalainen H, Hatakka K, Vapaatalo H, et al. Yoghurt containing galactooligosaccharides facilitates defecation among elderly subjects and selectively Increases the number of bifidobacteria. Int J Prob Preb. 2009;4:65–74.
    1. Tan PK, Downey TJ, Spitznagel EL, Xu P, Fu D, Dimitrov DS, et al. Evaluation of gene expression measurements from commercial microarray platforms. Nucleic Acids Res. 2003;31:5676–5684.
    1. Turnbaugh PJ, Hamady M, Yatsunenko T, Cantarel BL, Duncan A, Ley RE, et al. A core gut microbiome in obese and lean twins. Nature. 2009;457:480–484.
    1. Vanhoutte T, Huys G, Brandt E, Swings J. Temporal stability analysis of the microbiota in human feces by denaturing gradient gel electrophoresis using universal and group-specific 16S rRNA gene primers. FEMS Microbiol Ecol. 2004;48:437–446.
    1. Wagner M, Smidt H, Loy A, Zhou J. Unravelling microbial communities with DNA-microarrays: challenges and future directions. Microb Ecol. 2007;53:498–506.
    1. Watanabe K, Kodama Y, Harayama S. Design and evaluation of PCR primers to amplify bacterial 16S ribosomal DNA fragments used for community fingerprinting. J Microbiol Methods. 2001;44:253–262.
    1. Weis BK, Consortium MOTTR. Standardizing global gene expression analysis between laboratories and across platforms. Nat Methods. 2005;2:351–356.
    1. Wilson KH, Wilson WJ, Radosevich JL, DeSantis TZ, Viswanathan VS, Kuczmarski TA, Andersen GL. High-density microarray of small-subunit ribosomal DNA probes. Appl Environ Microbiol. 2002;68:2535–2541.
    1. Zoetendal EG, Akkermans AD, de Vos WM. Temperature gradient gel electrophoresis analysis of 16S rRNA from human fecal samples reveals stable and host-specific communities of active bacteria. Appl Environ Microbiol. 1998;64:3854–3859.
    1. Zoetendal EG, Collier CT, Koike S, Mackie RI, Gaskins HR. Molecular ecological analysis of the gastrointestinal microbiota: a review. J Nutr. 2004;134:465–472.
    1. Zoetendal EG, Vaughan EE, de Vos WM. A microbial world within us. Mol Microbiol. 2006a;59:1639–1650.
    1. Zoetendal EG, Heilig HGHJ, Klaassens ES, Booijink CCGM, Kleerebezem M, Smidt H, de Vos WM. Isolation of DNA from bacterial samples of the human gastrointestinal tract. Nat Protocols. 2006b;1:870–873.
    1. Zoetendal EG, Rajilić-Stojanović M, de Vos WM. High throughput diversity und functionality analysis of the gastrointestinal tract microbiota. Gut. 2008;57:1605–1615.

Source: PubMed

Sponsors et collaborateurs

Les conditions médicales

Interventions en matière de drogue

3
S'abonner