Supplementary data for Micro-eukaryotic diversity in the gut Scanlan and Marchesi: optimization of DNA extraction method and selection of primers used in this study
DNA extraction methods
Ten randomly selected faecal samples were selected for DNA extraction and PCR primer selection and optimisation.
Method A
This method is outlined in detail in the full text paper.
Method B
The following method represents a modified method of Qiagen stool extraction for pathogen detection. 200 mg of faecal sample was placed in a 2 ml tube containing a 200mg mixture of 0.1 mm, 0.5 and 2mm zirconium beads and 1.5 ml of ASL buffer. Samples were bead beaten at 3200 rpm for 90 s followed by heating to 95 C for 10 min. The rest of the protocol was followed as per manual and DNA was analysed as for Method A.
Method C
Fastprep DNA extraction kit was employed as per manufacturer’s instructions. DNA was analysed as for Method A.
PCR of 16S rRNA genes
All PCRs in this study were performed using the Taq polymerase kit (Invitrogen) and conducted in a MJ Research PTC-200P Thermal Cycler. PCR of partial 16S rRNA genes using the primers 968f-GC and 1401r was conducted as an initial test to assess the purity and integrity of the DNA extraction and also to calculate bacterial indexes of diversity to assess each DNA extraction method. 16S rRNA gene PCR mixtures of 50 μl contained 1 X Buffer (20 mM Tris pH 8.4, 50 mM KCl), 3 mM MgCl2, 200 µM of each dNTP, 1.25 U of Taq polymerase (Invitrogen, UK), and 10 pmol of each primer. Appropriately diluted DNA (5 ng) was added to the final PCR mix and 16S PCR cycling conditions were: 95ºC for 5 min initial denaturation, followed by 30 cycles of amplification at 95ºC denaturation for 30 s, 56 ºC annealing temperature for 40 s and extension of 72ºC for 1 min, with a final extension of 72ºC for 5 min.
Denaturing Gradient Gel Electrophoresis (DGGE) analysis
16S rRNA gene PCR products were separated according to the specifications of Muyzer and co-workers ( Muyzer et al., 1993) using the DCODE system (Bio-Rad Laboratories, UK) with the following modifications: Polyacrylamide gels (dimensions, 200 mm ´ 200 mm ´ 1 mm) consisted of 8% v/v polyacrylamide (37.5:1 acrylamide-bisacrylamide) and 0.5 X TAE. The final denaturant gradient for primer pair 968f-GC and 1401r was optimised to 30-55%. Prior to polymerisation of the denaturing gel a stacking gel without denaturants was added to enable defined wells to be cast. Electrophoresis was performed for 16 h at 85 V in 0.5 X TAE buffer at a constant temperature of 60ºC. Gels were stained with Sybergold® according to the manufacturer’s instructions.
Calculation of diversity indices using Biodiversity Pro
Composite datasets for bacterial DGGE profiles from each samples were generated and numerical band matching character tables produced for export and analysis by BiodiversityPro (version 2, Scottish Association for Marine Science, [http://www.sams.ac.uk]). Using the BiodiversityPro software, Shannon-Weaver and ecological indices of diversity were generated as previously published (Scanlan et al., 2008; Scanlan et al., 2006)
Results and Discussion
To test the efficiency of the three DNA extraction methods bacterial indexes of diversity were calculated from respective DGGE profiles and DNA concentration was determined. Although eukaryotic results for Method A and Method B were in agreement (numbers of bands on Eukaryotic DGGE profiles and diversity of sequences recovered), DNA extraction Method A gave the greatest DNA yield and had higher mean bacterial indexes of diversity compared to B. Method C gave a much lower mean DNA yield compared to both Method A and B with reduced bacterial diversity on DGGE profiles and failure to amplify strong eukaryotic and fungal PCR products using the primer pair Euk 1A and Euk 516r-GC and ITS1F and ITS4R. Data presented in this study is from the analysis of DNA extractions generated using Method A. However, due to agreement on data generated from both Method A and Method B both methods are suitable for the analysis of eukaryotic communities in the gastrointestinal tract.
Primer selection
A critical part of this study was to choose suitable PCR primers for the amplification eukaryotes in the human GI tract. One major hurdle was the potential to amplify background bacterial, plant/animal and human DNA which are all potentially represented in human faecal DNA extractions.
Seven different published eukaryotic or fungal specific PCR primers set were tested, see Table S1. Gradient PCR and MgCL2 titrations were performed on a range of bacterial and fungal DNA extracts, followed by PCR on faecal DNA extractions. Each primer set was tested on eight different human faecal DNA extractions, followed by DGGE/acrylamide electrophoresis and clone library construction to obtain sequence data.
For all primer sets with the exception of Euk 1A and Euk 516r-GC and ITS1F and ITS4R poor band resolution on DGGE or polyacrylamide electrophoresis and more importantly the results of sequence analysis of clone libraries generated for each primer set indicated that the products of all other primer sets were non-specific/non-fungal/non-eukaryotic products and therefore deemed unsuitable for studying the eukaryotic/fungal communities in the human gut.
This data, combined with analysis in silico of primer sequences indicated that the primer set Euk1A and Euk516r and ITS1F and ITS4R were the most suitable for analyzing eukaryotic diversity in the GI tract of humans. The random sequencing clones from the healthy controls yielded the partial sequence for small subunit ribosomal RNA belonging to Blastocystis sp. Following this result, seven more individuals were selected for clone library construction and analysis. The random sequencing of clones from each individual revealed that Blastocystis sp. accounted for all clones and that one library was dominated by Saccharomyces cerevisiae. In addition one plant (probably partially or undigested plant substrate from diet) and one human 18S rRNA gene sequence were retrieved. Fungal products were retrieved for sequences generated from the construction of fungal clone libraries. However, in two libraries smaller non specific products were generated but these could be easily discriminated by size difference. Otherwise these primers were the most suitable for the amplification of fungi from the human gastrointestinal tract.
Table S1. Primers tested in this study
Primera / Sequence (5'-3') / Specificity / Product size / Reference1406f / TGY ACA CAC CGC CCG T / Universal 16S/18S rRNA / Variable / (Fisher and Triplett, 1999)
3126r / ATA TGC TTA AGT TCA GCG GGT / Eukarya 28S rRNA / Variable / (Ranjard et al., 2001)
Euk1A / CTG GTT GAT CCT GCC AG / Eukarya 18S rRNA / 560 bp / (Sogin and Gunderson, 1987)
Euk 516r-(GC)a / ACC AGA CTT GCC CTC C / Eukarya 18S rRNA / 560 bp / (Amann et al., 1990)
Euk 1209f / CAG GTC TGT GAT GCC C / Eukarya 18S rRNA / 210 bp / (Giovannoni et al., 1988)
Uni 1392r-(GC)a / ACG GGC GGT GTG TRC / Universal 16S/18S rRNA / 210 bp / (Lane et al., 1985)
FRI / AIC CAT TCA ATC GGT AIT / Fungal 18S / 1648 bp / (Vainio and Hantula, 2000)
NS1 / Gta gtc ata tgc ttg tct c / Fungal 18S / 1648 bp / (White et al., 1990)
1406f / TGY ACA CAC CGC CCG T / Universal 16S/18S rRNA / Variable / (Fisher and Triplett, 1999)
3126r / ATA TGC TTA AGT TCA GCG GGT / Eukarya 28S rRNA / Variable / (Ranjard et al., 2001)
ITS-1F / CTT GGT CAT TTA GAG GAA GTA A / Fungal ITS / Variable / (Gardes and Bruns, 1993)
ITS-4R / TCC TCC GCT TAT TGA TAT GC / Fungal ITS / Variable / (White et al., 1990)
NL1 / GCA TAT CAA TAA GCG GAG GAA AAG / Fungal ITS / Variable / (O'Donnell, 1992)
NL4 / GGT CCG TGT TTC AAG ACG G / Fungal ITS / Variable / (O'Donnell, 1992)
a GC indicates a 40bp GC rich sequence attached to the 5' end of the primer: 5'–CCCGCCGCGCCCCGCGCCCGTCCCGCCGCCCCCGCCCG-3'
References
Amann RI, Binder BJ, Olson RJ, Chisholm SW, Devereux R, Stahl DA (1990). Combination of 16S ribosomal-RNA-targeted oligonucleotide probes with flow-cytometry for analyzing mixed microbial-populations. Appl Environ Microbiol 56: 1919-1925.
Fisher MM, Triplett EW (1999). Automated approach for ribosomal intergenic spacer analysis of microbial diversity and its application to freshwater bacterial communities. App Environ Microbiol 65: 4630-4636.
Gardes M, Bruns TD (1993). ITS primers with enhanced specificity for basidiomycetes--application to the identification of mycorrhizae and rusts. Mol Ecol 2: 113-8.
Giovannoni SJ, Delong EF, Olsen GJ, Pace NR (1988). Phylogenetic group-specific oligodeoxynucleotide probes for identification of single microbial-cells. J Bacteriol 170: 720-726.
Lane DJ, Pace B, Olsen GJ, Stahl DA, Sogin ML, Pace NR (1985). Rapid-determination of 16s ribosomal-rna sequences for phylogenetic analyses. PNAS USA 82: 6955-6959.
O'Donnell K (1992). Ribosomal DNA internal transcribed spacers are highly divergent in the phytopathogenic ascomycete Fusarium sambucinum (Gibberella pulicaris). Curr Genet 22: 213-20.
Ranjard L, Poly F, Lata JC, Mougel C, Thioulouse J, Nazaret S (2001). Characterization of bacterial and fungal soil communities by automated ribosomal intergenic spacer analysis fingerprints: biological and methodological variability. App Environ Microbiol 67: 4479-4487.
Scanlan PD, Shanahan F, Clune Y, Collins JK, O'Sullivan GC, O'Riordan M et al (2008). Culture-independent analysis of the gut microbiota in colorectal cancer and polyposis. Environ Microbiol 10: 789-98.
Scanlan PD, Shanahan F, O'Mahony C, Marchesi JR (2006). Culture-independent analyses of temporal variation of the dominant fecal microbiota and targeted bacterial subgroups in Crohn's disease. J Clin Microbiol 44: 3980-8.
Sogin ML, Gunderson JH (1987). Structural diversity of eukaryotic small subunit ribosomal RNAs. Evolutionary implications. Ann N Y Acad Sci 503: 125-39.
Vainio EJ, Hantula J (2000). Direct analysis of wood-inhabiting fungi using denaturing gradient gel electrophoresis of amplified ribosomal DNA. Mycol Res 104: 927-936.
White TJ, Bruns TD, Lee S, Taylor JW (1990). Amplification and direct sequencing of fungal ribosomal RNA genes for phylogenetics. In: Innis MA, Gelfand DH, Sninsky JJ and White TJ (eds). PCR Protocols: A Guide to Methods and Applications. Academic: New York. pp 315-322.