Comparative analysis of human gut microbiota by barcoded pyrosequencing - PubMed (original) (raw)
Comparative Study
Comparative analysis of human gut microbiota by barcoded pyrosequencing
Anders F Andersson et al. PLoS One. 2008.
Abstract
Humans host complex microbial communities believed to contribute to health maintenance and, when in imbalance, to the development of diseases. Determining the microbial composition in patients and healthy controls may thus provide novel therapeutic targets. For this purpose, high-throughput, cost-effective methods for microbiota characterization are needed. We have employed 454-pyrosequencing of a hyper-variable region of the 16S rRNA gene in combination with sample-specific barcode sequences which enables parallel in-depth analysis of hundreds of samples with limited sample processing. In silico modeling demonstrated that the method correctly describes microbial communities down to phylotypes below the genus level. Here we applied the technique to analyze microbial communities in throat, stomach and fecal samples. Our results demonstrate the applicability of barcoded pyrosequencing as a high-throughput method for comparative microbial ecology.
Conflict of interest statement
Competing Interests: The authors have declared that no competing interests exist.
Figures
Figure 1. Variability within the 16S rRNA gene.
From pre-aligned sequenced >1200 bp downloaded from RDP, the variability, measured as Shannon information entropy, was calculated at each sequence position, using only positions without a gap in E. coli. The graph shows the Shannon entropy (y-axis) averaged over 50 bp windows, centered at each position in the gene (x-axis). Shannon entropy at position x was calculated as –Σ p(xi) log_2 p_(xi), where p(xi) denotes the frequency of nucleotide i. The filled arrows indicate positions of the PCR primers, the dashed arrow the direction of sequencing.
Figure 2. Taxonomic classification accuracy.
Distribution of sequence distances (measured over the whole sequence lengths) between original sequence and the selected reference sequence, when 59 bp corresponding to minimal pyrosequencing reads were extracted from 1000 randomly selected RDP sequences and assigned to reference RDP sequences according to the procedure described in the Materials and Methods section (in this case the 1000 sequences had first been removed from the BLAST database).
Figure 3. Comparison of the throat, stomach and fecal microbiotas.
a, A neighbor joining phylogenetic tree of the RDP sequences representing the 454 reads from six samples of throat, stomach, and feces, respectively, was constructed. Branches in the tree represented in throat, stomach, and feces are labeled with green, yellow, and red, respectively. b, Hierchical clustering of the 18 samples based on how their reads were distributed within the tree using the weighted UniFrac metric for pair wise comparisons of the samples. The lower three samples are H. pylori positive stomachs.
Figure 4. Rarefaction analysis of the different gut ecosystems.
Number of phylotypes sampled as a function of number of reads. The data points represent averages of 1000 randomized samplings without replacements.
Similar articles
- Microarray analysis and barcoded pyrosequencing provide consistent microbial profiles depending on the source of human intestinal samples.
van den Bogert B, de Vos WM, Zoetendal EG, Kleerebezem M. van den Bogert B, et al. Appl Environ Microbiol. 2011 Mar;77(6):2071-80. doi: 10.1128/AEM.02477-10. Epub 2011 Jan 21. Appl Environ Microbiol. 2011. PMID: 21257804 Free PMC article. - Diet strongly influences the gut microbiota of surgeonfishes.
Miyake S, Ngugi DK, Stingl U. Miyake S, et al. Mol Ecol. 2015 Feb;24(3):656-72. doi: 10.1111/mec.13050. Mol Ecol. 2015. PMID: 25533191 - Primer Design for an Accurate View of Picocyanobacterial Community Structure by Using High-Throughput Sequencing.
Huber P, Cornejo-Castillo FM, Ferrera I, Sánchez P, Logares R, Metz S, Balagué V, Acinas SG, Gasol JM, Unrein F. Huber P, et al. Appl Environ Microbiol. 2019 Mar 22;85(7):e02659-18. doi: 10.1128/AEM.02659-18. Print 2019 Apr 1. Appl Environ Microbiol. 2019. PMID: 30709827 Free PMC article. - The pig gut microbial diversity: Understanding the pig gut microbial ecology through the next generation high throughput sequencing.
Kim HB, Isaacson RE. Kim HB, et al. Vet Microbiol. 2015 Jun 12;177(3-4):242-51. doi: 10.1016/j.vetmic.2015.03.014. Epub 2015 Mar 23. Vet Microbiol. 2015. PMID: 25843944 Review. - Microbial ecology in the age of genomics and metagenomics: concepts, tools, and recent advances.
Xu J. Xu J. Mol Ecol. 2006 Jun;15(7):1713-31. doi: 10.1111/j.1365-294X.2006.02882.x. Mol Ecol. 2006. PMID: 16689892 Review.
Cited by
- Dysbiosis of the Upper Gastrointestinal Tract in Head-and-Neck Cancer Survivors: A Pilot Study Using the Capsule Sponge Device.
Zeber-Lubecka N, Kulecka M, Dabrowska M, Kluska A, Piątkowska M, Turkot MH, Pilonis ND, Yusuf A, Nowicki-Osuch K, Mikula M, Ostrowski J. Zeber-Lubecka N, et al. Cancers (Basel). 2024 Oct 18;16(20):3528. doi: 10.3390/cancers16203528. Cancers (Basel). 2024. PMID: 39456621 Free PMC article. - High accuracy meets high throughput for near full-length 16S ribosomal RNA amplicon sequencing on the Nanopore platform.
Lin X, Waring K, Ghezzi H, Tropini C, Tyson J, Ziels RM. Lin X, et al. PNAS Nexus. 2024 Oct 9;3(10):pgae411. doi: 10.1093/pnasnexus/pgae411. eCollection 2024 Oct. PNAS Nexus. 2024. PMID: 39386005 Free PMC article. - Gastrointestinal cancer resistance to treatment: the role of microbiota.
Kolahi Sadeghi L, Vahidian F, Eterafi M, Safarzadeh E. Kolahi Sadeghi L, et al. Infect Agent Cancer. 2024 Oct 5;19(1):50. doi: 10.1186/s13027-024-00605-3. Infect Agent Cancer. 2024. PMID: 39369252 Free PMC article. Review. - Pollution gradients shape microbial communities associated with Ae. albopictus larval habitats in urban community gardens.
Duval P, Martin E, Vallon L, Antonelli P, Girard M, Signoret A, Luis P, Abrouk D, Wiest L, Fildier A, Bonnefoy C, Jame P, Bonjour E, Cantarel A, Gervaix J, Vulliet E, Cazabet R, Minard G, Valiente Moro C. Duval P, et al. FEMS Microbiol Ecol. 2024 Oct 25;100(11):fiae129. doi: 10.1093/femsec/fiae129. FEMS Microbiol Ecol. 2024. PMID: 39327012 Free PMC article. - Effect of Helicobacter pylori on sleeve gastrectomy and gastric microbiome differences in patients with obesity and diabetes.
Park YS, Ahn K, Yun K, Jeong J, Baek KW, Park DJ, Han K, Ahn YJ. Park YS, et al. Int J Obes (Lond). 2024 Nov;48(11):1664-1672. doi: 10.1038/s41366-024-01611-6. Epub 2024 Aug 24. Int J Obes (Lond). 2024. PMID: 39179750 Free PMC article.
References
- Savage DC. Microbial ecology of the gastrointestinal tract. Annu Rev Microbiol. 1977;31:107–133. - PubMed
- Wostmann BS, Larkin C, Moriarty A, Bruckner-Kardoss E. Dietary intake, energy metabolism, and excretory losses of adult male germfree Wistar rats. Lab Anim Sci. 1983;33:46–50. - PubMed
- Turnbaugh PJ, Ley RE, Mahowald MA, Magrini V, Mardis ER, et al. An obesity-associated gut microbiome with increased capacity for energy harvest. Nature. 2006;444:1027–1031. - PubMed
- Rakoff-Nahoum S, Paglino J, Eslami-Varzaneh F, Edberg S, Medzhitov R. Recognition of commensal microflora by toll-like receptors is required for intestinal homeostasis. Cell. 2004;118:229–241. - PubMed
Publication types
MeSH terms
Substances
LinkOut - more resources
Full Text Sources
Other Literature Sources