Supplementary Materials for:
Metabolic interdependencies between phylogenetically novel fermenters and respiratory organisms
in an unconfined aquifer
Kelly C. Wrighton, Cindy J. Castelle, Michael J. Wilkins, Laura A. Hug, Itai Sharon, Brian C. Thomas,
Kim M. Handley, Sean Mullin, Carrie D. Nicora, Andrea Singh, Mary S. Lipton, Philip E. Long, Kenneth
H. Williams, Jillian F. Banfield*
* Corresponding Author: jbanfield@berkeley.edu
This PDF file includes:
I. Supplementary Text and Methods
Genomic Binning
Phylogenetic Analyses
Genome Bins ACD17 and ACD79
Open-access data sharing
Metabolic analyses
Changes in relative abundance across the 10-day acetate stimulation
CRISPR/CAS autoimmunity
II. Supplementary Figures S1-S3, S6-S10
III. Supplementary Tables S4-S5
IV. Captions for Additional Supplementary Materials
V. References for Supplementary Materials
VI. Additional (separate documents) Supplementary Materials for this manuscript
Figure S4
Figure S5
Table S1
Table S2
Table S3
FASTA file for Figures S8 and S9
1
I. Supplementary Text and Methods
Genomic Binning.
We first used tetranucleotide signal to cluster genomic fragments via ESOM (main text). For
genome fragments > 10 kb, it was possible for 5 kb segments to fall into more than one cluster, especially
if segment ESOM positions fell close to cluster boundaries. Fragments were only binned ‘confidently’ if
> 50% of segments deriving from a genome fragment fell into the same cluster. In addition to
tetranucleotide information, we used abundance changes over time to inform genomic binning. We
computed the fraction of reads contributing to each contig from each dataset (A, C, and D) separately for
all genome fragments > 5 kb (read abundances were normalized to account for differences in the sizes of
the A, C and D genomic datasets). We projected the abundance ratio information ([A]/[D]) onto the
ESOM to further differentiate ESOM clusters. The set of genome segments comprising each genome bin
was exported by manually defining the boundaries in the ESOM and the region assigned an “ACD”
cluster number.
After completing ESOM binning as detailed in the main text methods, we were left with three sets
of contigs unbinned: (i) those of 10 – 15 kb (represented by exactly 2 segments), where the two segments
fell into different bins, and (ii) other fragments that had no bin assignment because they did not meet the
>50% requirement for other reasons (e.g., when fragments fell into multiple different map regions) (iii)
scaffolds < 5 kb. In case (i), fragments were assigned to one of the two bins randomly, but designated
“p” (e.g., assigned as ACD11p). Many of these were checked to rule out obvious discrepancies in GC
content and coverage. Scaffolds of type (ii) were named ACDUNK (ACD unknown) and all larger
fragments (> 20 kb) were binned after genomic annotation via phylogenetic analysis and based on
coverage (for very high coverage scaffolds). Some ACDUNK scaffolds were assigned to phylum-level
groups (e.g., ACDOP11), others to ACDNov if no phylogenetic classification was possible. Scaffolds in
case (iii) were binned by projection onto the ESOM map using their tetranucleotide frequency
information.
A histogram of sequence length and abundance ratio in the first (A) and last samples (D) shows
well-resolved peaks, indicating differential abundance patterns of genomes across experimental time
(Figure S2B). Peaks in the histogram were used to assign a color (representing the abundance ratio in
samples A/D) to each data point in the ESOM (Figure S2C). In some cases (e.g., clusters 2 and 3),
temporal abundance information assisted with the separation of adjacent clusters of fragments with
similar tetranucleotide sequence composition. In total, 87 genome bins were identified (Figure S2D),
while the remaining unbinned genome fragments were assigned to 13 bins of uncertain, but putative
identification. This data is available on the ACD ggKbase website (see data sharing below).
Phylogenetic analyses.
For the concatenated 16 ribosomal proteins, each individual gene dataset was aligned using MUSCLE
version 3.8.31 (Edgar RC, 2004) and then manually curated to remove end gaps and single-taxon
insertions. Model selection for evolutionary analysis was determined using ProtTest3 (Darriba et al.,
2011) for each single gene alignment. The curated alignments were concatenated to form a 16-gene, 729
taxa alignment with 3,544 unambiguously aligned positions. A maximum likelihood phylogeny for the
concatenated alignment was conducted using PhyML (Guindon et al., 2003) under the LG+α+γ model of
evolution and with 100 bootstrap replicates. FASTA of all nucleotide and protein sequences in the
genomes:
http://ggkbase.berkeley.edu/genome_summaries/88-ISME_Wrighton_GenomeCompletion
For single protein trees (e.g NiFe and FeFe hydrogenase), the phylogenetic pipeline was
performed as previously described (Wrighton et al., 2012). Briefly protein sequences were aligned using
MUSCLE version 3.8.31 with default settings (Edgar RC, 2004). Problematic regions of the alignment
were removed using very liberal curation standards according to (Sassera et al., 2011) with the program
2
GBlocks (Talavera et al., 2007). Alignments with and without GBlocks were confirmed manually. Best
models of amino acid substitution for each protein alignment were estimated using ProtTest3 (Darriba et
al., 2011). Phylogenetic trees were generated using RAxML (Stamatakis A, 2006) with the PROTCAT
setting for the rate model and the best model of amino acid substitution specified by ProtTest. Nodal
support was estimated based on 100 bootstrap replications using the rapid bootstrapping option
implemented in RAxML.
Genome Bins ACD17 and ACD79.
One bin, ACD79, contained several genes of functional interest including genes for carbon
utilization (Table S2) and NiFe hydrogenases (Figure S8), but contained only a few core genes for
assigning phylogenetic affiliation (Figure S3). Moreover, phylogenetic genes that were present provided
an inconsistent signal, indicating the bin was not representive of a single genome. For instance, many of
the ribosomal proteins affiliated with Firmicutes (~16x coverage), while RecA (~20x coverage) was
clearly associated with the phylum Chlamydiae. Coverage in the bin ranged from 3x to greater than 50x,
consistent with a genomic bin composed of multiple genomes. Many of the key genes discussed in this
manuscript are on small contigs less than five genes (e.g. cellobiose and NiFe hydrogenase), which do not
have accurate phylogenetic markers for assigning these functions to a taxonomic identity. As such we
conclude the ACD79 genomic bin contains genome fragments from several organisms; and assign these
fragments to unknown phylogenetic affiliation.
Another genomic bin (ACD17) also had a limited amount of marker genes, but those that were
present (e.g. RpoB, S7, L3) had strong coherent phylogenetic affiliation with members of the Chlamydiae.
Our proteomic data does suggest the presence and expression of Chlamydiae genes (from ACD17) in the
aquifer. This finding was unexpected; given all members of the phylum Chlamydiae are obligate
intracellular endosymbionts of Eukaryotes. When considering possible hosts, protozoan are likely
candidates as the nearest related genome to ACD17 (Table 1) has protozoan hosts in other aquifer
systems (Rolf et al., 2005), and recent 18S rRNA gene sequences collected from the Rifle aquifer
revealed an abundant and diverse protozoan community (Holmes et al., 2013). Future research is
necessary to untangle the obligate and facultative symbioses that may occur across the subsurface
microbial community.
Open-access data sharing.
An overview of the genomes reconstructed (ACD1 – ACD87), showing the bin size, number of
proteins predicted, average genome length/protein, phylogenetic affiliation (if known), average GC
content, largest scaffold, and average coverage by read depth. The “abundance” estimate was determined
based on genome coverage calculated from kmer coverage using the standard formula for interconverting
these quantities. Note that these values may not estimate the true abundance of any organism in the
community, because approximately 55.3% of the reads were not assembled during ACD genome
assembly and some organisms have contigs <2 kb which may not be binned.
Genomic bins can be accessed by clicking on the links for any of these ACD bins or by searching
for specific genes in the search tool bar. After signing in users can create “lists” with text, EC number, or
sequences (later via BLAST) as search terms. Additionally, these list features can be summarized using
“genome summary” feature, which can provide access to DNA and amino acid sequence FASTA files.
The binned data is included on the website:
http://ggkbase.berkeley.edu/Rifle_ACD/organisms
Metabolic analyses.
While we previously identified the capacity for fermentation in at least five candidate phyla (SR1,
WWE3, OD1, OP11, BD1-5, PER), our prior analyses did not include detailed summary of the carbon
degradation capacity across these genomes (Wrighton et al., 2012). Here we identified glycoside
hydrolases of selected functional classes (e.g. chitin, cellulase, debranching) by pfam HMM from all the
3
ACD bins. We then parsed this list for those that had high sequence similarity to a specific EC number.
The remaining sequences, which could not be assigned to an EC number, were left with a putative
designation based on pfam HMM classification. Both EC- and pfam-binned sequences are accounted for
in Table S2, while Figure 3 summarizes the EC and pfam data into one summary value. The column
entitled ‘Genome Phylogenetic Assignment’ includes taxonomic assignment and totals for each bin. All
DNA and protein sequence data supporting GH analysis can be accessed via a genome summary on the
website:
http://ggkbase.berkeley.edu/genome_summaries/80-ISME_Wrighton_CarbonDegradationProfile
We also examined genes for central carbon metabolism and the possible generation of
fermentation end-products. First we examined genomes for presence of genes for glycolysis and TCA
cycle. We then examined enzymes for converting pyruvate to acetyl-CoA via pyruvate dehydrogenase,
pyruvate-formate lyase, and pyruvate ferredoxin oxidoreductase. Also included are genes for possible
conversion of acetyl-CoA to ethanol, lactate, acetate, and butyrate (summarized in main text). We also
highlight potential FeFe hydrogenases and NiFe hydrogenases, but note Figures S8 and S9 are based on
manually curated data from these lists. We recognize many of these processes are reversible and only
attempt to identify directionality in our near-complete genomic bins that lack evidence for respiratory
metabolism (e.g. complete TCA cycle, pyruvate dehydrogenase, and electron transport machinery
including complex 1).
Of the carbon cycling organisms shown in Figure 5, we could only recover oxygen reductase
genes from ACD77, a member of the Bacteroidetes. This genome has components of an aerobic
respiratory chain including a cytochrome bd-type oxidase (ACD77_C00106G00003 and
ACD77_C00106G00004). This bd-type terminal oxidase is composed by two subunits: subunit I and
subunit II and contains three prosthetic hemes. The two genes identified in ACD77 are homologous to
those of CydA (subunit I) and CydB (subunit II), respectively, of the cytochrome bd-type quinol oxidases
from E. coli (42 and 26% identities, respectively). The heme-only cytochrome bd-oxidase is associated
with microaerobic oxygen respiration (Richter et al., 2003). However, the this complex is also found in
strictly anaerobic microorganism such Moorella thermoacetica, where it is been protects against oxidative
stress and thus contributes to the limited O2 tolerance of M. thermoacetica (Amaresh et al., 2005).
ACD77 has a partial NADH dehydrogenase (subunits D, E, F, C, B, A are present). However, given the
partial nature of this genome, many required subunits (M, N, L involved in protons translocation and J, K,
H, I and G) were not recovered.
Our analyses recovered five FeFe hydrogenases in the ACD dataset, three from ACD20 (novel
phylum) and two from ACD77 (Bacteroidetes) (Figure S7). Of the three confurcating hydrogenases in
ACD20, ACD20_18461 has all the necessary residues for functionality (L1, L2, and L3 motifs).
ACD20_9246_G0007, ACD20_9246_G0010, ACD77_9475.354011, and ACD77_9475.354011 contain
all three motifs but have a replacement of a serine by cysteine in motif 1 (TSCSPGW rather than
TSCCPAW), have a conserved replacement in motif 2 (MPCTAKFFE rather than MPCTAKKAE), and
ACD20_9246_G0010 has a replaced cysteine in motif 3 with isoleucine. Phylogenetic analyses based on
reference sequences from Schmidt et al. (2010) and recent database searches confirmed that the
hydrogenase sequences were most closely related (58-72% AAI) to those from fermentative organisms
(most obligately) including members of the Bacteroidetes (e.g. Anaerophaga thermohalophila),
Clostridium spp., and Spirochaetes (Figure S7). Notably, two hydrogenase clusters, located on ACD20
contig 9246 and ACD77 contig 9475, share synteny and similarity, with the large subunit sequences from
ACD77 and ACD20 more similar to each other (70%), than they are to homologs encoded on their
respective contigs (~45%) (Figure S7).
Previously we reported on and modeled type 4 and type 3b NiFe hydrogenases from OD1 and
OP11 (Wrighton et al., 2012). Here we continue that analysis across the remaining 29 non-CP ACD
genomes. Our phylogenetic analyses include only those sequences whose large catalytic subunit
sequences contained at least one amino acid motif for functionality and are at least 60% complete (less
than 75% sequences denoted as partial on tree). Sequences deposited as part of this analysis are in red,
4
those reported previously in green (OP11) and purple (OD1) (Figure S9). Complete amino acid FASTA
files for ACD and reference sequences used to generate Figure S8 and S9 are available as a supplemental
file.
Multi-heme cytochromes were identified by manual and automatic curation via conserved
CXXCH heme domains. Predicted phylogenetic affiliation, total heme content, and predicted cellular
localization from PSORTb are included in Table S3. Sulfur and nitrogen functional genes were identified
by annotation then confirmed manually. DNA or protein sequences can be accessed by searching GGKB
website for gene loci provided in Tables S3-S5.
Given the expression of genes indicative of active sulfate-reduction across our three time points,
we evaluated the functional likelihood of the dissimilatory sulfite reductase complex (DsrAB) via
modeling (Figure S7). Only the medium coverage DsrAB operon was complete enough to model. The
DsrA was most closely related to a sequence from D. psychrophila LVS4 (95% AAI) and the DsrB from
an unknown sulfate reducing bacterial sequence recovered from a contaminated aquifer in China (86%
AAI). Protein modeling using using Swiss-model (Bordoli et al., 2009) with Desulfomicrobium
norvegicum (DsrAB 65% AAI) confirmed that the substrate binding site, all cysteines coordinating the
[4Fe-4S] clusters, and siroheme cofactors are conserved (Figure S7). The remaining predicted DsrAB
partial protein sequences have high similarity to DsrAB in physiologically confirmed sulfate reducing
bacteria, suggesting the protein products are functional (Table S4).
In addition to the nitrate reductases recovered from genomes closely related to organisms with
physiological capabilities (ACD10 and ACD23), the capacity for nitrate reduction (narGHIJ) was also
confirmed in ACD75 contigs assigned to the Desulfobulbaceae. While the NarG was a partial sequence,
we could verify the five conserved catalytic residues and the homology to nitrate reductase in other sulfate
reducers, with a highest similarity to NarG from Desulfobacterium autotrophicum HRM2 (78% AAI).
However, D. autotrophicum has not been documented to use nitrate as a terminal electron acceptor
(Brysch et al., 1987), so the relevance to ACD75 physiology, and sulfate-reducing bacteria in general, is
currently unknown. Currently, only one other member of the Desulfobulbaceae, Desulfobulbus
propionicus, is known to grow by the reduction of nitrate (with propionate and sulfite as electron donors)
via a periplasmic nitrate reductase (Widdel and Pfenning, 1982; Greene et al., 2003).
Changes in relative abundance across the 10-day acetate stimulation.
Microbial community structure was determined for the initial sampling (5 days after acetate, light
blue bar), middle sampling (7 days after acetate, black triangle) and last sampling (10 days after acetate,
dark blue) using the coverage of the scaffold containing the single copy ribosomal protein S3 (Figure S6).
Two organisms, Dechloromonas spp. (ACD10) and a member of the Desulfobulbaceae (ACD75),
increase in abundance dramatically at the second time point, when the Fe(II) concentration is highest.
Specific members of BD1-5 (ACD3 and ACD4), OD1-i (ACD1, 5, 8, 11), and Deltaproteobacteria
(ACD75 and ACD53) increase in abundance with increasing amendment time, yet other members of these
same taxonomic groups show a decrease in abundance with time (Figure S6). These findings suggest that
certain taxa respond to acetate availability, however strong interdependencies would be hard to identify
with these data alone. For example, some taxa may respond to increased abundance of acetate-respiring
bacteria, yet themselves may not be able to utilize acetate.
CRISPR/Cas Adaptive phage immunity.
Given the recovery of phage genomic data, and the detection of expressed phage genes in situ
(Table 1), we examined CRISPR/Cas adaptive phage immunity across the data set. We only detected
evidence for two or more Cas proteins in one member of each of the OP11, OD1, and BD1-5 Candidate
phyla, and in a small subset of other Bacteria (ACD10, ACD23, ACD34, ACD39, ACD47, ACD60,
ACD62, ACD75, ACD79). Interestingly, the ACD79 mixed genome bin contains 25 Cas proteins.
Previous estimates, based primarily on isolate genome surveys, suggest that about 40 % of bacteria have
CRISPR loci (Jansen et al., 2002; Stern et al., 2010). The current study would suggest that these systems
5
are relatively underrepresented in the Candidate Phyla. Surprisingly, no spacer sequences extracted from
the CRISPR loci matched (even imperfectly) to any phage or other sequence in the dataset, raising the
possibility of other (possibly as yet unrecognized) defense mechanisms in these organisms. However, it is
also possible that the detected phage may be targeting bacteria retained on the 1.2 µm filter whereas
phage targeting the genomes sampled here may have passed through the 0.2 µm filter.
6
II. Supplementary Figures
Figure S1. A. Groundwater was collected during secondary acetate stimulation, meaning the aquifer was
also amended with acetate the year prior. Dotted red box in part A. is highlighted in B., which details the
well geochemistry during sample collection. Metagenomic samples (A, C, D) were collected 5, 7, and 10
days from the start of secondary acetate amendment during iron reduction.
7
8
Figure S2. A. ESOM constructed using tetranucleotide frequency information for fragments > 5 kb in
length. Boundaries (dark bands) separate regions (collections of genome fragments) with similar
signatures (each 5 kb fragment appears as a dot). B. Abundance ratios of fragments >5 kb in the A and C
samples from the time series. Specific abundance ratio ranges were assigned colors for application to the
ESOM. C. Gradation of color (shown in B.) was used to code the abundance ratio for each fragment
represented on the map to better define cluster boundaries. D. Discrete map regions were numbered (1 –
87, corresponding to ACD1 – ACD87). The red box shows the periodic repeat of the map. Unresolvable
regions were not binned from the ESOM (see SOM).
9
Figure S3. Genome completeness estimates for all recovered genomic bins. Bins that contain >75% of the
markers or more than one genome are included in part A, while part B contains the less complete
genomes. This figure and the FASTA files that accompany it can be accessed here:
http://ggkbase.berkeley.edu/genome_summaries/88-ISME_Wrighton_GenomeCompletion
10
11
Figure S6. Rank abundance profiles of ribosomal protein S3 (rpS3) defined phylotypes identified in the
initial sample A (light blue bar chart), the middle sample C (triangle symbol), and last sample D (dark
blue bar chart). The coverage of the rpS3-containing scaffold is plotted on the y-axis and the x-axis
contains organisms organized left to right by their abundance in sample A. Taxonomic affiliation is noted
by color symbol above the initial sample and below the rank abundance curve. Figure shows that low
abundant organisms (e.g. ACD3, ACD1) in time point 1 become dominant in time point 3.
12
Figure S7. Maximum likelihood tree of FeFe hydrogenase large catalytic subunit sequences. The five
ACD sequences from Bacteroidetes (ACD77) and a novel phylum (ACD20) are highlighted in red bold.
Reference sequences are in black with nearest neighbors included based on BLAST against the NCBI nr
database (May 2013). Bootstrap values (>50) are shown, based on 100 resamplings.
13
0.1
gi169257881 EDS71847 Anaerofustis stercorihominis DSM 17244
gi149905277 ABR36110 Clostridium beijerinckii NCIMB 8052
gi160624920 ABO425432 Clostridium butyricum
gi488597 AAA85785 Clostridium saccharobutylicum
gi50344697dbjBAD29951 Clostridium paraputrificum
gi169296709 EDS78838 Clostridium perfringens
80
56
gi188498603 ACD51739 Clostridium botulinum E3 str Alaska E43
54
gi118134934 ABK61978 Clostridium novyi NT
gi144836 AAA23248 Clostridium pasteurianum
61
gi557064 AAB03723 Clostridium acetobutylicum ATCC 824
100
gi146347733 EDK34269 Clostridium kluyveri DSM 555
99
gi209170690 ACI42788 Clostridium tyrobutyricum
gi150272145 EDM99349 Pseudoflavonifractor capillosus ATCC 29799
gi167665067 EDS09197 Anaerotruncus colihominis DSM 17241
gi167656200 EDS00330 Eubacterium siraeum DSM 15702
gi167660893 EDS05023 Clostridium scindens ATCC 35704
gi160430589 ABX44152 Clostridium phytofermentans ISDg
gi158440937 EDP18661 Clostridium bolteae ATCC BAA 613
gi145848527 EDK25445 Ruminococcus torques ATCC 27756
gi210149924 EEA80933 Clostridium nexile DSM 1787
gi158140165 ABW18477 Alkaliphilus oremlandii OhILAs
gi145410445 ABP67449 Caldicellulosiruptor saccharolyticus DSM 8903
gi125713088 ABN51580 Clostridium thermocellum ATCC 27405
gi219999973 ACL76574 Clostridium cellulolyticum H10
gi149951660 ABR50188 Alkaliphilus metalliredigens QYMF
gi14250935embCAC39231 Eubacterium acidaminophilum
gi167704730 EDS19309 Clostridium ramosum DSM 1402
100
gi169292311 EDS74444 Clostridium spiroforme DSM 1552
gi169247661 ACA51661 Thermoanaerobacterium saccharolyticum JW/SL YS485
gi206738217 ACI17295 Coprothermobacter proteolyticus DSM 5265
gi214035763 EEB76457 Carboxydibrachium pacificum DSM 12653
70
85 gi166855001 ABY93410 Thermoanaerobacter sp X514
gi166856698 ABY95106 Thermoanaerobacter pseudethanolicus ATCC 33223
gi158440918 EDP18642 Clostridium bolteae ATCC BAA 613
Spirochaeta smaragdinae DSM 11293 YP 003802215
85
88
100
97
73
88
57
78
97
90
68
100
74
ACD20 9246704834G0007
Phaeospirillum molischianum
ACD77 9475354011G0004
75
100
95
100
100
57
65
51
88
65
98
52
78
100
95
90
100
DSM 120 ZP 09877549
Anaerophaga thermohalophila DSM 12881 ZP 08845406
gi134052208 ABO50179 Desulfotomaculum reducens MI 1
gi121307228 EAX48145 Thermosinus carboxydivorans Nor1
gi83573467 ABC20019 Moorella thermoacetica ATCC 39073
gi169638340 ACA59846 Desulforudis audaxviator MP104C
gi206743093 ACI22150 Thermodesulfovibrio yellowstonii DSM 11347
gi169637214 ACA58720 Desulforudis audaxviator MP104C
gi85722031 ABC76974 Syntrophus aciditrophicus SB
gi114338877 ABI69725 Syntrophomonas wolfei
Pelotomaculum thermopropionicum strain SI YP 001212560
gi146274442dbjBAF60191 Pelotomaculum thermopropionicum SI
gi134053819 ABO51790 Desulfotomaculum reducens MI 1
gi149948338 ABR46866 Alkaliphilus metalliredigens QYMF
gi118133456 ABK60500 Clostridium novyi NT
gi187773177 EDU36979 Clostridium sporogenes ATCC 15579
gi160359833 ABX31447 Petrotoga mobilis SJ95
gi212676039 EEB35646 Anaerococcus hydrogenalis DSM 7454
gi115252467embCAJ70310 Clostridium difficile 630
100
gi164602497 EDQ95962 Clostridium bartlettii DSM 16795
100
gi164604047 EDQ97512 Clostridium bartlettii DSM 16795
gi160428861 ABX42424 Clostridium phytofermentans IS
100
gi164604201 EDQ97666 Clostridium bartlettii DSM 1
85
gi188500220 ACD53356 Clostridium botulinum E3 str
96
gi149903112 ABR33945 Clostridium beijerinckii NCIM
gi167660485 EDS04615 hydrogenase Fe only Alistipes putredinis DSM 17216
gi149936113 ABR42810 Parabacteroides distasonis ATCC 8503
100
99 gi218224548 EEC97198 Parabacteroides johnsonii DSM 18315
gi154085279 EDN84324 Parabacteroides merdae ATCC 43184
gi77545287 ABA88849 poss Pelobacter carbinolicus DSM 2380
100
gi77545315 ABA88877 poss Pelobacter carbinolicus DSM 2380
79
gi466366 AAA87057 Desulfovibrio fructosovorans
gi189435405 EDV04390 Bacteroides intestinalis DSM 17393
100
gi29337426
AAO75231 Bacteroides thetaiotaomicron VPI 5482
73
95 gi149129481 EDM20695 Bacteroides caccae ATCC 43185
gi156107991 EDO09736 Bacteroides ovatus ATCC 8483
Symbiobacterium thermophilum IAM14863 BAD42191
gi51858033dbjBAD42191 Symbiobacterium thermophilum IAM 14863
gi169638544 ACA60050 Desulforudis audaxviator MP104C
gi146273809dbjBAF59558 Pelotomaculum thermopropionicum SI
gi167591797 ABZ83545 Heliobacterium modesticaldum Ice1
100
100 gi94448908embCAJ44289 Heliobacillus mobilis
Heliobacillus mobilis CAJ44289
gi219992456 ACL69059 Halothermothrix orenii H 168
gi160360253 ABX31867 Petrotoga mobilis SJ95
ACD77 9475354011G0001
ACD20 9246 70483 14G0010
gi177840576 ACB74828 Opitutus terrae PB90 1
gi186971103 ACC98088 Elusimicrobium minutum Pei191
gi57225451 AAW40508 poss Dehalococcoides ethenogenes 195
100gi73659815embCAI82422 poss Dehalococcoides sp CBDB1
gi146269821 ABQ16813 Dehalococcoides sp BAV1
gi89336906dbjBAE86501 poss Desulfitobacterium hafniense Y51
98
gi134051038 ABO49009 Desulfotomaculum reducens MI 1
65
gi146273100dbjBAF58849 Pelotomaculum thermopropionicum SI
87
gi169637216 ACA58722 Candidatus Desulforudis audaxviator MP104C
gi6650985 AAF22114 Megasphaera elsdenii DSM 20460
100
gi158434701 EDP12468 Clostridium bolteae ATCC BAA 613
88
gi167662588 EDS06718 Clostridium scindens ATCC 35704
81
gi150274152 EDN01243 Pseudoflavonifractor capillosus ATCC 29799
85
gi167654850 EDR98979 Anaerostipes caccae DSM 14662
gi169297952 EDS80043 Clostridium perfringens
gi149905080 ABR35913 Clostridium beijerinckii NCIMB 8052
70
gi146346356 EDK32892 Clostridium kluyveri DSM 555
gi115252370embCAJ70211 Clostridium difficile 630
85
100
gi164604064 EDQ97529 Clostridium bartlettii DSM 16795
gi51858116dbjBAD42274 Symbiobacterium thermophilum IAM 14863
gi83573631 ABC20183 Moorella thermoacetica ATCC 39073
gi50875368embCAG35208 poss Desulfotalea psychrophila LSv54
93
gi78217927 ABB37276 Desulfovibrio alaskensis G20
gi114338374 ABI69222 Syntrophomonas wolfei subsp wolfei str Goettingen
gi116697357 ABK16545 Syntrophobacter fumaroxidans MPOB
100
67
gi1914864embCAA72423 Desulfovibrio fructosovorans JJ
100
gi13022069 AAK11625AF331719 Desulfovibrio alasken
77
78
gi46449596 AAS96246 Desulfovibrio vulgaris Hildenboroug
gi206741320 ACI20377 Thermodesulfovibrio yellowstonii DS
100
gi167353361
ABZ75974
Shewanella halifaxensis HAW EB4
100
gi24350246 AAN56895 Shewanella oneidensis MR 1
85
70gi117611495 ABK46949 Shewanella sp ANA 3
gi88660702 ABD48098 Shewanella decolorationis
85
gi113886266 ABI40318 Shewanella sp MR 4
gi187438956 ACD10930 Blastocystis sp NandII
gi149793997 ABR31445 Thermosipho melanesiensis BI429
100
gi154152871 ABS60103 Fervidobacterium nodosum Rt17 B1
92
gi157314808 ABV33907 Thermotoga lettingae TMO
53
gi147735403 ABQ46743 Thermotoga petrophila RKU 1
100
gi170176047 ACB09099 Thermotoga sp RQ2
gi115519803 ABJ07787 Rhodopseudomonas palustris BisA53
100
gi46449598 AAS96248 Desulfovibrio vulgaris Hildenborough
gi217991372 EEC57378 Bacteroides pectinophilus ATCC 43243
gi188498811
ACD51947 Clostridium botulinum E3 str Alaska E43
87
100
gi210154580 EEA85586 Clostridium hiranonis DSM 13275
55
gi167655182 EDR99311 Anaerostipes caccae DSM 14662
91
gi167710039 EDS20618 Clostridium sp SS2/1
100
gi41817525 AAS12110 Treponema denticola ATCC 35405
93
gi166028598 EDR47355 Dorea formicigenerans ATCC 27755
58
gi167662445 EDS06575 Clostridium scindens ATCC 35704
67
gi210152607 EEA83613 Clostridium nexile DSM 1787
gi149752498 EDM62429 Dorea longicatena DSM 13814
gi134052211 ABO50182 Desulfotomaculum reducens MI 1
gi149792909 ABR30357 Thermosipho melanesiensis BI429
66
gi154152860 ABS60092 Fervidobacterium nodosum Rt17 B1
100
gi217336057 ACK41850 Dictyoglomus turgidum DSM 6724
72
gi157314419 ABV33518 Thermotoga lettingae TMO
68
gi221572431 ACM23243 Thermotoga neapolitana DSM 4359
100
96 gi147736041 ABQ47381 Thermotoga petrophila RKU 1
gi4981990 AAD36496AE001794 Thermotoga maritima MSB8
gi170287484dbjBAG14005 Termite group 1 bacterium phylotype Rs D17
100
gi118502624 ABK99106 Pelobacter propionicus DSM 2379
100
100
64
74
90
100
59
68
100
ACD20 18461244044G0012
73
74
100
100
87
100
100
99
100
100
73
80
gi156864730 EDO58161 Clostridium sp L2 50
gi167653849 EDR97978 Anaerostipes caccae DSM 14662
gi153794181 EDN76601 Ruminococcus gnavus ATCC 29149
gi149831165 EDM86254 Ruminococcus obeum ATCC 29174
gi166027777 EDR46534 Dorea formicigenerans ATCC 27755
gi158434681 EDP12448 Clostridium bolteae ATCC BAA 613
gi158140225 ABW18537 Alkaliphilus oremlandii OhILAs
gi125713176 ABN51668 Clostridium thermocellum ATCC 27405
gi56387327 AAV86076 Clostridium saccharoperbutylacetonicum ATCC 27021
gi160426914 ABX40477 Clostridium phytofermentans ISDg
gi182378378 EDT75909 Clostridium butyricum 5521
gi149905387 ABR36220 Clostridium beijerinckii NCIMB 8052
gi188498443 ACD51579 Clostridium botulinum E3 str Alaska E43
14
72
100
Grp3
52
76
100
85
56
mo
na
lo
ro
ch
De
Grp3c putative YP001717784
Desulforudis audaxvia
79
Grp3c Deha
lococcoides
Grp3c
ethenogenes
a NP
YP 848
195
6135
058 Syn
Grp3
53
c YP
Grp3
tropho
0647
bacter
a Me
4Des
Q0thanop
fumaro
ulfo
xidans
Gr Grp3 0404 yrus
tale
MPO
p3 c
kand
Met
a ps
c
Y
ychr
NP P447 hanoc leri AV
ophi
27
occ
la LS
19
62 369
us
v54
Met
62
vol
han
tae
Me
th
os
ph a
an
ot
era
YP
h
e
0
rm
sta
YP03
ob
dtm
ac
0052
an
te
Gr
ae
3842
r
p3
DSM
th
4731
er
3 6 Si AC d A
30
ma
91
6 de D1 AD3
ut
ot
80
Ga ro 0
ro
65
8
l l xy
ph
R
ic
i o d a 91
us
97 hodo
ne ns
De
ba
ll l i
lt H
ct
a
th 25
a
e
r
51
ca ot
ca
ps ro
ps
6G
ul
i f ph
00
at
er icu
u
01
s
ri
s
fo
ES
p
1
rm
ar
an
ti
s
al
ES
2
eobacteria
ACD62 30930 12218 13G0001 Deltaprot
xi
546 7078
ACD34 223
fle
05
tial Chloro terium MLMS1
9 N
bac
si
7G0006 par
53
teo
abys 1
pro
AB
hrix ed OP3
7 Delta
GC
ldit
129175
SC
ltur 00
81 Ca
ve ZP0
Uncu 6G0 eon
5509
ZP09
5558 81 1 rcha
BAL5
3 6 le s a
tive
a
0 88
at
113 oplasm
rm
The
A CD
tive
ta
c pu
100
70
3C
92
B
B1
RC
AM
a
ic
um
at
ic
12
om
et
H6
gn
ar
ma
um
m
il
xi
o
ph
lu
le
om
mo
il
er
of
or
ir
th
or
hl osp
l
c
s
mu
Ch
De net
1
lo
g
8
3
U NI
og
Ma
20
00
la
ty
84 759
G0 mophi
ic
4
2
9
D
r
4
LSv5
YP 22
the
97
59
la
d YP4
50 inea
51
phi
p3 d
002
22
chro
PCC7
Grrp3
95 erol
00
psy
sp
G
YP 876 Ana
ea
cus
00
ve
ococ
otal
ti 34 736
ulf
nech
02
ta CD 41
Des 469 Sy
24
75
s DSM110
Pu A YP00 948
PCC
ovoran
1733
d
65
peptid
p3 rp3d YP 0 d YP002 Nostoc
io
r
ibr
G
G
d Grp3 7520
sulfov
Grp3 d YP0070
7 Dethio
DSM13181
639310
m mobile
Grp3
ve ZP0
Anaerobaculu
594
Putati
6444
3d
Grp d Putative YP00
BAA1850
Grp3
Anaerobaculum hydrogeniformans
Grp3d Putative ZP06439013
s
na
100
85
98
68
95
78
53
3D
59
9777
100
98
79
62
ACD22 38087 6568 19G0008 OP11
004 OP11
28 5419 7G0
ACD57 914
92
3B
53
92
70
100
99
63
100
60
95
AH
T
1
47 75 i
DSM113
ss
stonii
by
180 ix a
o yellow
ovibri
DSM ithr
us SB
a
desulf
phic
sum
Thermo
ld
ri
itro
49644
vino 2 Caea
acid
te
YP0022
phus
Grp3b
ialomatium 69269i8amat bac D1i
ntro
t
Sy
r
o O
t
pa lochr
0173
00
WP dus
YP46
te
004
ro 01
1G0 2786 Al
ab
rh
4 2
a p 00
44
lo
319
003
mm 7G
Ha
YP
11
4
5
Ga
74
371
e3b
66
a 23
tiv
52
22
08
ri DG1
0
08
0
Puta
0
0
4
WP
G
te m
8
10
ac r i u
28
74
ob cte
9
1
e
D
9
t ba
6
AC
ro e
55
ap bia
35
mm r o
1
D2
Ga omic
AC
01 rruc
0
0
e
6G 60 V
62
43
05
43
05
4
ZP
59
b
6
3
51
ve
ti
46
ta
Pu
CD
4
56
ct
e
r
al
ka
li
p
hi
l
us
1
th
i
ob
a
73
83
99
0
De
100
72
8
51
70
56
99
52
71
100
Gr
100
9
57
50
91
CC
AT
ca
ri
te
en
ns
la
ma
el
or
um
of
on
br
en
lm
og
ru
Sa
dr
m
1
lu s hy
il
64
u
38
ir erm
85
36
h
sp
tei
V7
t
a
o
M
ng
od xydo
AA
DS
hu
Rh
o
b
um
p4
us
11 Car
ll
Gr
os
ri
12
i
lu m
p
ri
45 64 7
os
cel
fu
AC 60
an
A
3
rmo
th
1
us
4 YP
the
Me
BAV
rp a
cc
6
um
G
8
sp
p4
co
idi
31
Gr
des
50
ro
str
coi
YP
lo
Py
ococ
1 C
p4
hal
gas
Gr
409
39
o gi
8 De
010 736
ibri
lfov
YP0 ABQ1
4
Desu
Grp Grp4 1029
AAP5
Grp4
3
16
65
74
100
83
p4
Pu
100
ACD14
Gr EEB
ta
PutativeGrp4 27 3422 42G0005 OD1i
Pu
100
ti
p4 73
ta
YP 113608
4
ve
ACD5 75
ti
Puta
Methylococcu
E E 25
Gr
ve
65
s capsulat
tiv
24 3130
Gr
p4
B7
T
eGr
p4
9G0003
29 her
ZP
p4
CA
mo
Pu
ACD ACD7 12
91
YP
OD
09
J7
t
c
0
9
a
25
3 14 1i
65
oc
tiv 0379
Gr T
362
23
29
cu
940
eG
984
p4 her
0
9
2
r
C
s
9
77
p4
6
an
171
Can
G001
sp
CA moc
De
di
NC1
57
did
1 OD
da
su
oc
A3
0
9
at
A
G00
1i
tu
lf
M4
bac
us
cu
55
s
04
os
Nitr
ter
s
Ku
50
po
OD1
iu
osp
en
sp
ro
1
i
m D
en
ira
si
ia
utc
Es
AM
def
nu
h
st
ch
4
luv
s
sed
ut
ii
er
yo
tg
ime
un
ic
ar
nt
gi
ti
hi
ae
e
ns
a
is
DS
co
M
li
17
73
4
100
NP
5
58
77
p4
71
65
Gr
AC
D7
100
51
100
3
2941
ATCC
ilis
riab
na va
abae
73102
me PCC
87 An
ctifor
3250
a YP
toc pun
Grp2
77 Nos
AAC162
Grp2a
5
100
8882
opersicina
capsa rose
0740 Thio
um japonicum USDA110
Grp2b GAAX4
rp2b NP773583 Bradyrhizobi
35
21
19
Gr
99
p1
6
YP
28 7
AC
06
91 2 9
D5
43
11
3
32 G 0 0
27
De
G0 01
su
79
AC D
l
3
00
f
Gr
ot
74
p
30
p1
6 97
YP0
16 alea 1 D art
01
67
e
p
i
24
229
24 6
G0 sych sul al
652
9 1
0
ro
fo D
Ge
ph
0
ob a 0 1
G
b e
Grp1
00 0
i
ZP07
2 p cter u Geob la L ulbsul
3354
art ran ac Sv5 ac fo
71
ial iire te 4 ae b
Desu
lfov
a ul
pladucer
ibri
ba
sm ns
o fr
ca
ucto id Rf4
so
ea
Grp1
vora
92
89
AC
D7
A
YP00
ns
3329
JJ
621
Grp1 YP3
Deha
loco
60377
ccoi
Carbox
des
ydothe
spVS
rmus hyd
rogeno
forman
sZ2901
Grp2b YP00
2526186 Rhod
obacter spha
eroides KD13
1
Grp2b AAC32033 Rhodobacter
capsulatus
at
i
ve
3
b
ZP
03
98
Pu
t
79
puta
70
72 9
EMR
ve
100
93
100
89
ACD
Grp3
GE5 D1
4070736 Ther
ios
mococcusus DSM363
barophil8us
53
MP
NP 579061 hydrogenaseII alpha
Pyrococcus furiosus DSM3638
ati
Grp3c put
at i
pu t
A
AC CD1
D9 1
12 1 2
D6
6 4
7
38 76 98
21
1 3
86 26 57
5
1 4 80
AC 479 9G5
D7
7 0 29
30 6G 013G0
0
2
4
69 004 OD77
04 O 1 i O
AC
D6
83 d1 D1
3
G0 i i 66
A CD
24
00
99
55
83
7
74
4
351
76
OD
43
80 8
97
1i 71
5
7 52
96
9G
A CD
5 6
0
58
G00 014
251
Grp3
21
O
05
b YP
1844
63 6
OD 1 D 1
82 Th
38
ermo
Grp3b
1 1G
cocc
NP1265
Grp3b
us
001
NP5786
48 Pyr
ko
23 Pyr
ococcu dakare
2 O
ococcu
s abyssi
nsis
Grp3b YP00
D1
s fur
KO
AC
c
Grp3
3c
Grp
1i i
ODODi1
1
08
00 04OD
8G G006
i
1 00 i D 1
47
91 65 9 G0 OD1 O
4
2
74 1 6 15
99
49 0 8 78 00 00
9 0 G
4
6
D1
K6 15 9G 9
AC
UN 3 4 3 5 1
D1 756 677 43
AC
8
17
6
29 1 7
D5
AC D5
99
AC 8
D
AC
0.1
s
Figure S8. Maximum likelihood tree of NiFe hydrogenase sequences with hydrogenase class groupings
(3B, 3C, 3D, 1, and 4) that contain ACD sequences highlighted in bold. ACD sequences previously
reported are colored purple (OD1) and green (OP11). ACD sequences reported as part of this manuscript
are in red. Reference sequences are in black and include those that have been physiologically confirmed
and nearest neighbors that lack physiological confirmation (noted as putative). Bootstrap values (>50) are
shown, based on 100 resamplings.
15
Figure S9. A) In silico modeling of DsrAB from ACD75 (~40x coverage fragment) to the known
structure of Desulfomicrobium norvegicum (shown in B., PDB:2XSJ). The ACD75 medium-coverage
DsrA and DsrB sequences have 66% and 65% amino acid identity with the corresponding subunits from
D. norvegicum. The four [4Fe-4S] clusters from the complex DsrAB are colored in black and the two
sirohemes are colored in red.
16
Figure S10. Proteomic expression of sulfate reduction genes across the three time points, with key genes
expressed as early as five days after acetate stimulation (sample A). Three distinct copies of the putative
sulfate reduction pathway were identified from scaffolds with high (>65X), medium (~40X), and low
coverage (<10X). Grey box indicates the gene was not identified in the metagenome. All scaffolds were
from the ACD75 bin and located on contigs with closest relationship to members of the
Desulfobulbaceae.
17
III. Supplementary Tables
Table S4. Dissimilatory sulfite reductase genes identified in the ACD metagenome.
Gene ID
Subunits
Length
(aa)
% of identity
% of identity
% of identity
Best hits in NCBI (blastP)
Desulfomicrobium
Archaeoglobus
fulgidus (PDB:
3MMC)
Desulfovibrio
vulgaris
(PDB: 2V4J)
% of identity
Norvegicum (PDB:
2XSJ)
ACD75_2650.24017.53
G0028
Alpha subunit
117
38
45
38
71%
Chlorobium
(YP_910622)
ACD75_7481.6912.26G
0006
Alpha subunit
80
38
40
33
64% Pelodictyon
(YP_002019133)
ACD75_7481.6912.26G
0005
Alpha subunit
118
41
47
43
66%
Chlorobium
(YP_001960255)
ACD75_7481.6912.26G
0007
Beta subunit
144
36
44
40
76%
Prosthecochloris
(YP_002014743)
ACD75_2265.5038.64G
0001
Alpha subunit
151
61
49
62
93% uncultured prokaryote (AEZ49823)
ACD75_2265.5038.64G
0002
Beta subunit
375
64
54
63
87%
Desulfotalea
(YP_064534)
ACD75_5279.2885.33G
0001
Alpha subunit
216
39
45
39
64%
Chlorobium
(YP_001960255)
phaeobacteroides
ACD75_5279.2885.33G
0002
Beta subunit
358
42
47
45
75%
Chlorobium
(YP_910623)
phaeobacteroides
ACD75_142.16489.41G
0013
Beta subunit
375
65
55
63
86%
Desulfotalea
(YP_064534)
ACD75_142.16489.41G
0014
Alpha subunit
349
66
53
66
95% Uncultured sulfate
bacterium (ABK90687)
18
phaeobacteroides
phaeoclathratiforme
phaeobacteroides
aestuarii
psychrophila
psychrophila
reducing
Table S5. Key functional genes for relevant nitrogen metabolisms identified in the ACD metagenome. Genes greater than 75% of alignment
length are denoted as complete, less than 75% are partial.
Organism
Dechloromonas
ACD10
Dechloromonas
ACD10
Dechloromonas
ACD10
Dechloromonas
ACD10
Comamonadaceae
ACD23
Comamonadaceae
ACD23
Comamonadaceae
ACD23
Comamonadaceae
ACD23
Comamonadaceae
ACD23
Comamonadaceae
ACD23
Comamonadaceae
ACD23
Comamonadaceae
ACD23
Comamonadaceae
ACD23
Desulfobulbacaea
ACD75
Desulfobulbacaea
ACD75
Desulfobulbacaea
ACD75
Best hit against NR NCBI database (including percentage of identity, annotation,
Amino
amino acid length and accession number)
acid
length
ACD10 Dechloromonas: Nitrate and Nitrite Reduction
ACD10_59995.11181.12G0004
cytochrome c-type
161
62%
protein NapB
complete
Candidatus Accumulibacter phosphatis clade IIA str. UW-1 Nitrate reductase
cytochrome c-type subunit (NapB) (155aa) (YP_003169088)
ACD10_C00026G00001
periplasmic nitrate
365
89%
reductase NapA
partial
Dechloromonas aromatica RCB (periplasmic nitrate reductase subunit NapA) (837aa)
(YP_286714)
ACD10_19428.2894.19G0002
cytochrome d1, heme
561
93%
region
complete
Dechloromonas aromatica RCB (cytochrome d1, heme region)(561aa) (YP_286474)
ACD10_3191.2771.13G0001
cytochrome c, class
611
88%
I:cytochrome d1,
complete
Dechloromonas aromatica RCB (cytochrome c, class I:cytochrome d1, heme region)
heme region
(576aa) (YP_286522)
ACD23, a member of the Comamonadaceae: Nitrate, Nitrite, and Nitrous-oxide Reduction
ACD23_30478.2373.10G0001
nitrate reductase,
35
83%
alpha subunit
partial
Rhodoferax ferrireducens T118 (respiratory nitrate reductase alpha subunit) (1272aa)
(YP_524035)
ACD23_112229.2031.9G0004
Nitrate reductase,
38
97%
alpha subunit
partial
Acidovorax sp. KKS102 (nitrate reductase subunit alpha) (1265aa) (YP_006852832)
ACD23_120092.2114.10G0002
nitrate reductase 1,
166
100%
beta subunit
partial
Acidovorax radices (nitrate reductase A subunit beta) (507aa) (WP_010463003)
ACD23_120092.2114.10G0001
nitrate reductase, beta
153
82%
subunit
partial
Salmonella enterica (nitrate reductase subunit 2 beta) (547aa) (WP_006635366)
ACD23_120092.2114.10G0003
nitrate reductase, beta
84
84%
subunit
partial
Proteus penneri (hypothetical protein) (74aa) (WP_006535459)
ACD23_120092.2114.10G0004
nitrate reductase 1,
244
98%
alpha subunit
partial
Acidovorax delafieldii (nitrate reductase A subunit alpha) (1266aa) (WP_005795701)
ACD23_65655.2560.11G0002
nitrite reductase (NO572
85%
forming)
complete
Acidovorax sp. JS42 (nitrite reductase) (574aa) (YP_986168)
ACD23_25640.2198.11G0002
nosZ; nitrous-oxide
568
92%
reductase
complete
Acidovorax delafieldii (Nitrous-oxide reductase) (645aa) (WP_005797511)
ACD23_65655.2560.11G0002
nitrite reductase (NO572
85%
forming)
complete
Acidovorax sp. JS42 (nitrite reductase) (574aa) (YP_986168)
ACD75, member of the Desulfobulbaceae: Potential for Nitrate and nitric-oxide reduction, and NrfA
ACD75_7481.6912.26G0009
NarG, nitrate
219
69%
reductase 1, alpha
partial
Desulfotignum phosphitoxidans (nitrate reductase alpha chain) (668aa) (WP_006968765)
subunit
ACD75_1208.4520.27G0007
NarG, nitrate
164
78%
reductase 1, alpha
partial
Desulfotignum phosphitoxidans (nitrate reductase alpha chain) (561aa) (WP_006968766)
subunit
ACD75_2523.3723.38G0001
nitric-oxide reductase
393
44%
partial
Geobacillus kaustophilus HTA426 (nitric oxide reductase cytochrome b subunit) 9
Gene ID
Primary annotation
19
Desulfobulbaceae
ACD75
ACD75_11188.12436.33G0010
Desulfobulbaceae
ACD75
ACD75_11188.12436.33G0011
Desulfobulbaceae?
ACD75-small
contig (could be
misbin) yet high
coverage is
consistent with
ACD75
ACD75_C00095G00010
Desulfobulbaceae
ACD75
ACD75_2650.24017.53G0012
Geobacter
ACD53
ACD53_41450.4833.18G0001
Geobacter
ACD55
ACD55_37793.7867.12G0004
Geobacter
ACD75-misbin
moved to ACD55
ACD55_C00094G00007
Novel Deltaproteobacteria
ACD73
Bacteroidales
ACD77
ACD73_290737.2868.6G0004
ACD77_93884.135712.12G0038
hypothetical protein;
nitric-oxide
reductase,
cytochrome bcontaining subunit I
nitric-oxide
reductase,
cytochrome bcontaining subunit I
K04561 nitric-oxide
reductase,
cytochrome bcontaining subunit I
395
partial
nrfA; cytochrome
c552
498
complete
nrfA; cytochrome
c552
496
complete
(790aa) (YP_146611)
59%
Desulfomonile tiedjei DSM 6799 (nitric oxide reductase large subunit) (758aa)
(YP_006447466)
314
partial
70%
Desulfomonile tiedjei DSM 6799 (nitric oxide reductase large subunit) (758aa)
(YP_006447466)
111
partial
59%
Geobacter daltonii FRC-32 (nitric-oxide reductase) (774aa) (YP_002535496)
83%
Desulfobulbus propionicus DSM 2032 (respiratory nitrite reductase (cytochrome;
ammonia-forming)) (498aa) (YP_004195416)
Geobacter related Nitric-oxide reductase and NrfA
cytochrome c nitrite
61
100%
reductase, catalytic
partial
Geobacter sulfurreducens PCA (cytochrome c nitrite and sulfite reductase, catalytic
subunit NrfA
subunit lipoprotein) (490aa) (NP_954195)
norZ; nitric oxide
763
100%
reductase
complete
Geobacter bemidjiensis Bem (nitric oxide reductase (cytochrome b)) (763aa)
(cytochrome b)
(YP_002140689)
cytochrome c; nitric110
77%
oxide reductase,
partial
Geobacter bemidjiensis Bem (cytochrome c) (238aa) (YP_002138064)
cytochrome ccontaining subunit II
Other organisms nitrogen metabolism
periplasmic nitrate
148
54%
reductase NapA
partial
Maribacter sp. HTCC2170 (nitrate reductase catalytic subunit) (775aa) (YP_003861668)
20
69%
Parabacteroides goldsteinii (cytochrome C nitrite reductase subunit c552) (494aa)
(WP_007659437)
IV. Captions for separate supplementary materials
Figure S4. Complete maximum likelihood tree from Figure 2. The tree is based on sixteen ribosomal
protein gene alignments concatenated and manually curated to form a 3,544-position, 729-taxon
alignment. The ribosomal proteins used were rpL 2, 3, 4, 5, 6, 14, 15, 16, 18, 22, 24, and rpS3, 8, 10, 17,
and 19. The best substitution model was determined for each alignment using ProtTest, and all alignments
shared a common model of best fit. The complete concatenated tree was conducted using PhyML under
the LG+I+γ model of evolution with 100 bootstrap resamplings. Sequences including the moniker “ACD”
are from this dataset. Bootstrap support values of 50 or greater are included on the tree.
Figure S5. Lineage specific concatenated ribosomal protein trees with reference sequences from JGIIMG (05/01/13) in the lineage. A) Alphaproteobacteria B) Betaproteobacteria C) Gammaproteobacteria
D) Deltaproteobacteria E) Spirochaeta F) Bacteroidetes.
Table S1. Summary of proteomic data for the A, C, and D samples (spectral count and normalized
spectral abundance factor (NSAF) values are reported. Results for organisms from the same lineage are
grouped, and within groups they are arranged approximately by protein abundance. Bold highlight flags
proteins identified by two or more peptides.
Table S2. Glycoside hydrolases (GH) identified by pfam domain/EC number in each of the ACD
genomic bins. In the cases where organisms contained more than one GH type, it was noted by ACD bin
number x and the number of GH identified (e.g. 77x2 denotes bin ACD77 has two GH). Parentheses
within the table text sum the total number of GH affiliated with each phyla: OD1, OP11, BD1-5, ACD20
and ACD47 novel Phyla (NOV), WWE3, Proteobacteria (Prot), Firmicutes (Firm), Chloroflexi (Chloro),
and GH in bins with unknown phylogenetic affiliation (UNKN). For some categories, no GH were not
detected (ND).
Table S3. Inventory of c-type cytochromes identified in the ACD metagenome including organism
affiliation, predicted subcellular localization, and heme content.
21
V. References for Supplementary Materials
Abascal F, Zardoya R, Posada D. (2005). ProtTest: selection of best-fit models of protein evolution.
Bioinformatics, 21(9), 2104–2105.
Brysch K, Schneider C, Fuchs G, Widdel F. (1987). Lithoautotrophic growth of sulfate-reducing bacteria,
and description of Desulfobacterium autotrophicum gen. nov., sp. nov. Archives of Microbiology,
148(4), 264–274.
Bordoli L, Kiefer F, Arnold K, Benkert P, Battey J, Schwede T. (2009). Protein structure homology
modeling using SWISS-MODEL workspace. Nat protoc 4, 1-13.
Darriba D, Taboada GL, Doallo R, Posada D. (2011) ProtTest 3: fast selection of best-fit models of
protein evolution. Bioinformatics 27, 1164-1165
Das A, Silaghi-Dumitrescu R, Ljungdahl LG, Kurtz DM. (2005). Cytochrome bd Oxidase, Oxidative
Stress, and Dioxygen Tolerance of the Strictly Anaerobic Bacterium Moorella thermoacetica. Journal
of bacteriology, 187(6), 2020–2029.
Edgar RC. (2004). MUSCLE: multiple sequence alignment with high accuracy and high throughput.
Nucleic Acids Research, 32(5), 1792–1797.
Greene EA, Hubert, C, Nemati M, Jenneman GE, Voordouw G. (2003). Nitrite reductase activity of
sulphate‐ reducing bacteria prevents their inhibition by nitrate‐ reducing, sulphide‐ oxidizing
bacteria. Environmental Microbiology, 5(7), 607–617.
Holmes DE, Giloteaux L, Williams KH, Wrighton KC, Wilkins MJ, Thompson CA, et al. (2013).
Enrichment of specific protozoan populations during in situ bioremediation of uranium-contaminated
groundwater. The ISME journal, 1–13.
Hyatt D, Chen GL, LoCascio PF, Land ML, Larimer FW, Hauser LJ (2010). Prodigal: prokaryotic gene
recognition and translation initiation site identification. BMC Bioinformatics, 11(1), 119.
Jansen R, Embden JD, Gaastra W, Schouls LM (2002). Identification of genes that are associated with
DNA repeats in prokaryotes. Molecular microbiology, 43(6), 1565–1575.
Michel R, MüLLER KD, Zoeller L, Walochnik J, Hartmann M, Schmid EN. (2005). Free-living amoebae
serve as a host for the Chlamydia-like bacterium Simkania negevensis. Acta protozoologica, 44(2),
113–121.
Richter OMH, Ludwig B. (2003). Cytochrome c oxidase: structure, function, and physiology of a redoxdriven molecular machine. Rev. Physiol. Biochem. Pharamacol. 147:47–74.
Sassera, D, Lo N, Epis S, D'Auria G, Montagna M, Comandatore F., et al. (2011). Phylogenomic
Evidence for the Presence of a Flagellum and cbb3 Oxidase in the Free-Living Mitochondrial
Ancestor. Molecular Biology and Evolution, 28(12), 3285–3296.
22
Schmidt O, Drake HL, Horn MA (2010). Hitherto unknown [Fe-Fe]-hydrogenase gene diversity in
anaerobes and anoxic enrichments from a moderately acidic fen. Applied and Environmental
Microbiology, 76(6), 2027–2031.
Stamatakis, A. (2006). RAxML-VI-HPC: maximum likelihood-based phylogenetic analyses with
thousands of taxa and mixed models. Bioinformatics, 22(21), 2688–2690.
Stern A, Keren L, Wurtzel O, Amitai G, Sorek R. (2010). Self-targeting by CRISPR: gene regulation or
autoimmunity? Trends in Genetics, 26(8), 335–340.
Talavera G, Castresana, J. (2007). Improvement of Phylogenies after Removing Divergent and
Ambiguously Aligned Blocks from Protein Sequence Alignments. Systematic Biology, 56(4), 564–
577.
Widdel F, Pfennig N. (1982). Studies on dissimilatory sulfate-reducing bacteria that decompose fatty
acids II. Incomplete oxidation of propionate by Desulfobulbus propionicus gen. nov., sp. nov.
Archives of Microbiology, 131(4), 360–365.
Wrighton KC, Thomas BC, Sharon I, Miller CS, Castelle CJ, VerBerkmoes NC, et al. (2012).
Fermentation, Hydrogen, and Sulfur Metabolism in Multiple Uncultivated Bacterial Phyla. Science,
337(6102), 1661–1665.
23