1
Supplementary data for Micro-eukaryotic diversity in the gut Scanlan and Marchesi:
2
optimization of DNA extraction method and selection of primers used in this study
3
4
DNA extraction methods
5
6
Ten randomly selected faecal samples were selected for DNA extraction and PCR primer
7
selection and optimisation.
8
9
10
Method A
This method is outlined in detail in the full text paper.
11
12
Method B
13
The following method represents a modified method of Qiagen stool extraction for pathogen detection.
14
200 mg of faecal sample was placed in a 2 ml tube containing a 200mg mixture of 0.1 mm, 0.5 and
15
2mm zirconium beads and 1.5 ml of ASL buffer. Samples were bead beaten at 3200 rpm for 90 s
16
followed by heating to 95 C for 10 min. The rest of the protocol was followed as per manual and DNA
17
was analysed as for Method A.
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19
Method C
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Fastprep DNA extraction kit was employed as per manufacturer’s instructions. DNA was analysed as for
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Method A.
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24
PCR of 16S rRNA genes
25
All PCRs in this study were performed using the Taq polymerase kit (Invitrogen) and conducted in a MJ
26
Research PTC-200P Thermal Cycler. PCR of partial 16S rRNA genes using the primers 968f-GC and
27
1401r was conducted as an initial test to assess the purity and integrity of the DNA extraction and also
28
to calculate bacterial indexes of diversity to assess each DNA extraction method. 16S rRNA gene PCR
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mixtures of 50 μl contained 1 X Buffer (20 mM Tris pH 8.4, 50 mM KCl), 3 mM MgCl 2, 200 µM of each
30
dNTP, 1.25 U of Taq polymerase (Invitrogen, UK), and 10 pmol of each primer. Appropriately diluted
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DNA (5 ng) was added to the final PCR mix and 16S PCR cycling conditions were: 95ºC for 5 min initial
32
denaturation, followed by 30 cycles of amplification at 95ºC denaturation for 30 s, 56 ºC annealing
33
temperature for 40 s and extension of 72ºC for 1 min, with a final extension of 72ºC for 5 min.
34
35
Denaturing Gradient Gel Electrophoresis (DGGE) analysis
36
16S rRNA gene PCR products were separated according to the specifications of Muyzer and co-
37
workers ( Muyzer et al., 1993) using the DCODE system (Bio-Rad Laboratories, UK) with the following
38
modifications: Polyacrylamide gels (dimensions, 200 mm  200 mm  1 mm) consisted of 8% v/v
39
polyacrylamide (37.5:1 acrylamide-bisacrylamide) and 0.5 X TAE. The final denaturant gradient for
40
primer pair 968f-GC and 1401r was optimised to 30-55%. Prior to polymerisation of the denaturing gel a
41
stacking gel without denaturants was added to enable defined wells to be cast. Electrophoresis was
42
performed for 16 h at 85 V in 0.5 X TAE buffer at a constant temperature of 60ºC. Gels were stained
43
with Sybergold® according to the manufacturer’s instructions.
44
45
Calculation of diversity indices using Biodiversity Pro
46
Composite datasets for bacterial DGGE profiles from each samples were generated and numerical
47
band matching character tables produced for export and analysis by BiodiversityPro (version 2, Scottish
48
Association for Marine Science, [http://www.sams.ac.uk]).
49
Shannon-Weaver and ecological indices of diversity were generated as previously published (Scanlan
50
et al., 2008; Scanlan et al., 2006)
Using the BiodiversityPro software,
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52
Results and Discussion
53
To test the efficiency of the three DNA extraction methods bacterial indexes of diversity were calculated
54
from respective DGGE profiles and DNA concentration was determined. Although eukaryotic results for
55
Method A and Method B were in agreement (numbers of bands on Eukaryotic DGGE profiles and
56
diversity of sequences recovered), DNA extraction Method A gave the greatest DNA yield and had
57
higher mean bacterial indexes of diversity compared to B. Method C gave a much lower mean DNA
58
yield compared to both Method A and B with reduced bacterial diversity on DGGE profiles and failure to
59
amplify strong eukaryotic and fungal PCR products using the primer pair Euk 1A and Euk 516r-GC and
60
ITS1F and ITS4R. Data presented in this study is from the analysis of DNA extractions generated using
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Method A. However, due to agreement on data generated from both Method A and Method B both
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methods are suitable for the analysis of eukaryotic communities in the gastrointestinal tract.
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64
Primer selection
65
A critical part of this study was to choose suitable PCR primers for the amplification eukaryotes in the
66
human GI tract. One major hurdle was the potential to amplify background bacterial, plant/animal and
67
human DNA which are all potentially represented in human faecal DNA extractions.
68
69
Seven different published eukaryotic or fungal specific PCR primers set were tested, see Table S1.
70
Gradient PCR and MgCL2 titrations were performed on a range of bacterial and fungal DNA extracts,
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followed by PCR on faecal DNA extractions. Each primer set was tested on eight different human faecal
72
DNA extractions, followed by DGGE/acrylamide electrophoresis and clone library construction to obtain
73
sequence data.
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75
For all primer sets with the exception of Euk 1A and Euk 516r-GC and ITS1F and ITS4R poor band
76
resolution on DGGE or polyacrylamide electrophoresis and more importantly the results of sequence
77
analysis of clone libraries generated for each primer set indicated that the products of all other primer
78
sets were non-specific/non-fungal/non-eukaryotic products and therefore deemed unsuitable for
79
studying the eukaryotic/fungal communities in the human gut.
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This data, combined with analysis in silico of primer sequences indicated that the primer set Euk1A and
82
Euk516r and ITS1F and ITS4R were the most suitable for analyzing eukaryotic diversity in the GI tract
83
of humans. The random sequencing clones from the healthy controls yielded the partial sequence for
84
small subunit ribosomal RNA belonging to Blastocystis sp. Following this result, seven more individuals
85
were selected for clone library construction and analysis. The random sequencing of clones from each
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individual revealed that Blastocystis sp. accounted for all clones and that one library was dominated by
87
Saccharomyces cerevisiae. In addition one plant (probably partially or undigested plant substrate from
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diet) and one human 18S rRNA gene sequence were retrieved. Fungal products were retrieved for
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sequences generated from the construction of fungal clone libraries. However, in two libraries smaller
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non specific products were generated but these could be easily discriminated by size difference.
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Otherwise these primers were the most suitable for the amplification of fungi from the human
92
gastrointestinal tract.
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Table S1. Primers tested in this study
a
Primera
Sequence (5'-3')
Specificity
Product size
Reference
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)
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)
GC
indicates
a
40bp
GC
rich
sequence
CCCGCCGCGCCCCGCGCCCGTCCCGCCGCCCCCGCCCG-3'
attached
to
the
5'
end
of
the
primer:
5'–
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: 720726.
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 315322.