SUPPLEMENTAL MATERIALS AND METHODS Construction of

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SUPPLEMENTAL MATERIALS AND METHODS
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Construction of reference and OTU phylogenies. A bacterial phylogeny suitable for use with
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the program pplacer was constructed by Kembel et al. (2012) using 16S sequences from the
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Greengenes database (DeSantis et al., 2006), but no such phylogeny was available for fungi. To
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construct the reference phylogeny for fungi, full and nearly full-length fungal LSU sequences
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from the Assembling the Fungal Tree of Life Project (Celio et al., 2007) were downloaded from
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the GenBank nucleotide database, aligned using MAFFT version 7.0 (Katoh & Standley, 2013)
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and then filtered to remove any position with > 15% gaps or variable bases in mothur (Schloss
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et al., 2009). A maximum-likelihood phylogeny was built using RAxML v 7.2.7 (Stamatakis et al.,
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2005), with the GTR + gamma + I model. To place environmental OTUs onto their respective
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reference phylogenies (maximum likelihood fungal LSU or bacterial 16S from Kembel et al.
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(2012), representative fungal and bacterial OTUs were aligned to their respective reference tree
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databases using PyNAST (Caporaso et al., 2010), with a BLAST cutoff of 0.6. Bacterial OTU
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sequences were masked using the Greengenes file from QIIME or the fungal LSU mask file
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generated during filtering of the AFTOL sequences as described above. Filtered fungal and
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bacterial OTU sequences were placed onto their respective reference trees using pplacer
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(Matsen et al., 2010). To visualize the distribution of active and dormant OTUs across the
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bacterial and fungal OTU phylogenies, we used the Interactive Tree of Life (itol.embl.de) to
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color branches based on classification of OTUs to the phylum level from the Ribosomal
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Database Project. OTUs classified with a bootstrap value less than 50% were colored in grey. An
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outer ring was then added to indicate the inferred state of each OTU based on the ratio of rRNA
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to rDNA (active, dormant, unknown; Supplemental Fig. 1A, 1B).
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Null model trials for patterns of phylogenetic clustering. We used two additional null models
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to determine of the patterns of phylogenetic clustering between active and dormant
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communities were robust. Using the ses.mpd script in the R package picante (Kembel et al.,
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2010) we selected a null model which randomized all taxa across the tips of the phylogeny
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(“taxa.labels in picante), and the independent swap model (“independentswap” in picante)
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based on the algorithm by Gotelli (2000). Each null model was run for 99 trials, using
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rarefaction to randomly sample the bacterial and fungal communities to their lowest sequence
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numbers (400 and 1000, respectively). Statistical analyses were conducted as described for the
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“frequency” null model described in the main text.
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SUPPLEMENTAL RESULTS
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Null models. Paired t-tests showed significant differences between the active and dormant
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bacterial communities using both the “independentswap” model (IS; t = 5.57, p < 0.001, DF = 8)
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and the “taxa.labels” model (TL; t = 3.82, p = 0.005). Similar patterns were found when
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comparing the rRNA versus the rDNA for these same models (IS: t = 10.84, p < 0.001, TL: 5.36, p
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< 0.001). We also found significant differences for fungal communities, with significantly higher
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clustering for the dormant and rDNA communities compared to the active and rRNA
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communities, respectively, the opposite of the pattern observed for bacteria. Significant
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differences were found between the active and dormant fungal community using the
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“independentswap” model (t = -11.8, p < 0.001, DF = 11) and the “taxa.labels” model (t = -4.01,
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p = 0.002), and these patterns held when the rRNA versus the rDNA communities were
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compared (IS: t = -4.74, p < 0.001, TL: t = -6.94, p < 0.001).
2
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Regression analysis using the additional null models showed significant correlations for
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the active bacterial communities for both pH (IS: F = 11.31, R2 = 0.56, p = 0.01, DF = 1,7, TL: F =
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33.1, R2 = 0.80, p < 0.001) and for carbon to nitrogen ratio (IS: F = 6.42, R2 = 0.40, p = 0.04, TL: F
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= 32.9, R2 = 0.80, p < 0.001). No correlations were found for either model with the dormant
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bacterial community (all p > 0.05). Analysis of the fungal communities likewise showed no
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significant correlations between any community (active or dormant) and either pH or carbon to
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nitrogen ratio, regardless of the null model used (all p > 0.05).
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References
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Caporaso JG, Bittinger K, Bushman FD, DeSantis TZ, Andersen GL, Knight R. (2010). PyNAST: a
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flexible tool for aligning sequences to a template alignment. Bioinformatics 26:266–267.
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Celio GJ, Padamsee M, Dentinger BTM, Bauer R, McLaughlin DJ. (2007). Assembling the Fungal
Tree of Life: constructing the Structural and Biochemical Database. Mycologia 98:850–859.
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DeSantis TZ, Hugenholtz P, Larsen N, Rojas M, Brodie EL, Keller K, et al. (2006). Greengenes, a
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chimera-checked 16S rRNA gene database and workbench compatible with ARB. Applied
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and Environmental Microbiology 72:5069–5072.
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Gotelli NJ. (2000). Null model analysis of species co-occurrence patterns. Ecology 81:2606–
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2621. http://www.esajournals.org/doi/abs/10.1890/0012-
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9658%282000%29081%5B2606%3ANMAOSC%5D2.0.CO%3B2.
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Katoh K, Standley DM. (2013). MAFFT multiple sequence alignment software version 7:
improvements in performance and usability. Mol Biol Evol 30:772–780.
Kembel SW, Cowan PD, Helmus MR, Cornwell WK, Morlon H, Ackerly DD, et al. (2010). Picante:
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R tools for integrating phylogenies and ecology. Bioinformatics 26:1463–1464.
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Kembel SW, Wu M, Eisen JA, Green JL. (2012). Incorporating 16S gene copy number information
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improves estimates of microbial diversity and abundance. Kembel, SW, Wu, M, Eisen, JA, &
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Green, JL (eds). PLoS Comput Biol 8:e1002743.
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http://dx.plos.org/10.1371/journal.pcbi.1002743.s004.
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Matsen FA, Kodner RB, Armbrust EV. (2010). pplacer: linear time maximum-likelihood and
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Bayesian phylogenetic placement of sequences onto a fixed reference tree. BMC
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Bioinformatics 11:538.
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Schloss PD, Westcott SL, Ryabin T, Hall JR, Hartmann M, Hollister EB, et al. (2009). Introducing
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mothur: open-source, platform-independent, community-supported software for
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describing and comparing microbial communities. Applied and Environmental Microbiology
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75:7537–7541.
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Stamatakis A, Ludwig T, Meier H. (2005). RAxML-II: a program for sequential, parallel and
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distributed inference of large phylogenetic trees. Concurrency Computat: Pract Exper
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17:1705–1723.
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SUPPLEMENTAL FIGURE LEGENDS
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Supplemental Fig. 1. Phylogenies of environmental OTUs for bacteria, A and fungi B using
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placement of representative OTUs onto reference phylogenies. The outer ring indicates
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classification of each OTU as either active (green), dormant (blue), or undetermined (red).
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Branch colors represent classification of OTUs to the phylum level using the RDP 16S bacterial
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or the LSU fungi databases. Branches of any OTU that was classified with a bootstrap value
4
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below 50% were colored in grey.
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Supplemental Fig 2. Mean phylogenetic clustering using the “independentswap” null model for
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bacterial communities, A and fungal communities, B and the “taxa.labels” null model for
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bacterial communities, C and fungal communities, D showed similar patterns to the
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“frequency” null model, although whether samples were significantly different from random
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using permutation tests varied depending upon which null model was used. As patterns were
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similar for active versus dormant and rRNA versus rDNA, only activity based comparisons are
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shown for clarity. Asterisks indicate significant differences based on paired t-tests.
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Supplemental Fig. 3. Regression analysis of active (black symbols) and dormant (grey symbols)
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communities using the “independentswap” null model (triangles) or the “taxa.labels” null
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model (squares). Significant correlations were found for the active bacterial communities across
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gradients of pH, A and carbon to nitrogen ratio, C, with no corresponding correlations found for
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the dormant community. No significant correlations were found for either the active or the
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dormant fungal communities across the pH, B or the carbon to nitrogen ratio, D environmental
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gradients.
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SUPPLEMENTAL FIGURES
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otu805
otu1059
otu316
otu2
otu129
otu217 8
otu180 9
otu409 2
otu18
otu83 08
otu52 5
otu19 0
otu30 52
otu20 6
otu51 87
otu9370
otu84
otu504
otu455
otu514
otu1409
otu1706
otu1328
otu190
otu552
9
otu533
otu229
otu139
6
otu647
2
otu178
otu136
3
otu107
0
otu134
2
otu726
otu145
otu193
5
otu167
7
otu749
otu693 7
otu230
otu62
5
otu4
otu1
394
otu7
65
otu1
54 2
otu2
94
otu2
18 8
otu5
31 1
otu5
45 4
otu4
46
otu2
52
otu7
12
otu1
45
otu8
15
otu1 90
otu8
76
otu1
66 4
otu6
42
otu4
91 8
otu6
63
otu1
69
otu8
06
otu1
61 5
otu7
29
otu1
64 7
otu6
50
otu1
88 8
otu1
29
otu4
22 5
otu1
77 3
otu7
40
ot
ot u1 80
ot u7 30
ot u1 12 7
ot u1 38
ot u1 33 5
ot u1 83 0
ot u2 12 9
ot u6 05 4
ot u4 44 7
ot u8 43
ot u1 78
ot u2 47
ot u1 27 4
ot u5 85 1
ot u6 26 7
ot u1 11
ot u8 65
ot u2 83 0
ot u1 10
ot u1 45 0
ot u1
o u2 35
ottu 03 3
ot 8127
o u2 8 3
o tuu8 16
o t 2184 0
o t u5 28
o tuu5 17
o tu 1 64
o t 2 07
o t u1 26 7
o t u4 13 4
ottuu15123 3
o
9
o t u1 3
o t u1 1 57
o t u 7 1 99
o t u2 6 26
o t u3 6 7
o t u1 6 5
o t u9 1 7
o t u1 6 1 2
o t u1 5 2
otu 85
o t u 12 8 1
ottuu11397048
oot u 22 2 5
ottuu21138363
oot u 16 2 1
ottuu21585557
o
ottuu34119 6
oottuu121425
oottuu11075904
oottuu2813063
oottuu7893331
oottuu516591
oottuu7618854
oottuu212398
ototuu215 1128
ootuu2130235 8
ototutu317 07434
u1166278 6
4 1 47
2
111
7
112
Fig. 2.
113
Bacteria
*
Active
*
A
*
114
Fungi
*
C
Dormant
B
Active
D
Dormant
115
116
8
117
Fig. 3.
Bacteria
Fungi
A
B
C
D
118
9
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