Matrix 1999 Itag
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Department of Geological and Planetary Sciences, California Institute of Technology, Pasadena, CA, United States DOI Published 2016-04-18 Accepted 2016-03-18 Received 2016-01-12 Academic Editor Subject Areas, Keywords Magneto-FISH, Co-occurrence network, Earth microbiome project, iTag sequencing, Anaerobic oxidation of methane, Microbial association, Microbial ecology Copyright © 2016 Trembath-Reichert et al. Licence This is an open access article distributed under the terms of the, which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed.
For attribution, the original author(s), title, publication source (PeerJ) and either DOI or URL of the article must be cited. Cite this article Trembath-Reichert E, Case DH, Orphan VJ. ( 2016) Characterization of microbial associations with methanotrophic archaea and sulfate-reducing bacteria through statistical comparison of nested Magneto-FISH enrichments.
PeerJ 4: e1913. Methane seep systems along continental margins host diverse and dynamic microbial assemblages, sustained in large part through the microbially mediated process of sulfate-coupled Anaerobic Oxidation of Methane (AOM).
This methanotrophic metabolism has been linked to consortia of anaerobic methane-oxidizing archaea (ANME) and sulfate-reducing bacteria (SRB). These two groups are the focus of numerous studies; however, less is known about the wide diversity of other seep associated microorganisms. We selected a hierarchical set of FISH probes targeting a range of Deltaproteobacteria diversity. Using the Magneto-FISH enrichment technique, we then magnetically captured CARD-FISH hybridized cells and their physically associated microorganisms from a methane seep sediment incubation. DNA from nested Magneto-FISH experiments was analyzed using Illumina tag 16S rRNA gene sequencing (iTag). Enrichment success and potential bias with iTag was evaluated in the context of full-length 16S rRNA gene clone libraries, CARD-FISH, functional gene clone libraries, and iTag mock communities.
We determined commonly used Earth Microbiome Project (EMP) iTAG primers introduced bias in some common methane seep microbial taxa that reduced the ability to directly compare OTU relative abundances within a sample, but comparison of relative abundances between samples (in nearly all cases) and whole community-based analyses were robust. The iTag dataset was subjected to statistical co-occurrence measures of the most abundant OTUs to determine which taxa in this dataset were most correlated across all samples. Many non-canonical microbial partnerships were statistically significant in our co-occurrence network analysis, most of which were not recovered with conventional clone library sequencing, demonstrating the utility of combining Magneto-FISH and iTag sequencing methods for hypothesis generation of associations within complex microbial communities. Network analysis pointed to many co-occurrences containing putatively heterotrophic, candidate phyla such as OD1, Atribacteria, MBG-B, and Hyd24-12 and the potential for complex sulfur cycling involving Epsilon-, Delta-, and Gammaproteobacteria in methane seep ecosystems. Introduction A central goal in microbial ecology is identifying and understanding microbial interactions in the environment. This goal can be addressed at many scales from statistical analyses of entire ecosystems (;;;; ) to high resolution image analysis of specific symbioses (;;;; ). Previous studies have shown that complex datasets can be distilled to determine primary ecosystem drivers, such as temperature, as main predictors of community variability.
In addition to correlating microbial patterns to environmental factors, interspecies interactions can be evaluated with methods such as co-occurrence analysis. Statistical significance of co-occurrence can be assessed at scales ranging from the entire genome to the operational taxonomic unit (OTU) (; ). Many physical separation methods have been developed to partition complex microbial assemblages before analysis, including fluorescence-activated flow sorting (; ), optical trapping , microfluidics , and immunomagnetic beads (; ) that use characteristics of interest such as phylogenetic identity (Fluorescence In Situ Hybridization; FISH) or activity (;;;; ).
Here we combine Magneto-FISH and Illumina Tag (iTag) sequencing utilizing the Earth Microbiome Project (EMP) universal primer set. The Magneto-FISH method was originally developed to enrich for and characterize multi-species microbial associations in environmental samples.
This method consists of a liquid CARD (CAtalyzed Reporter Deposition)-FISH reaction as a 16S rRNA gene identity-based selection mechanism followed by an immunomagnetic sediment matrix separation mechanism to target specific phylogenetic groups in conjunction with their physically associated microbial partners. By combining this method for phylogenetically targeted physical separation with high throughput amplicon sequencing, we can compare an array of associated microbial communities in parallel, with replicates. This provides statistical power in deriving microbial associations from complex sediment community assemblages, and thereby improving hypothesis development. Anaerobic methane-oxidizing (ANME) archaea and sulfate-reducing Deltaproteobacteria (SRB) are the predominant community members discussed in methane seep literature and form syntrophic partnerships in physical associations, termed “aggregates” or consortia (;;;; ). Since physical association appears to be an important element for consortia activity (; ), methods like Magneto-FISH are ideal for probing this system because target organisms are separated from the sediment matrix along with their physically associated partners. A hierarchical probe set was chosen targeting Deltaproteobacteria and their ANME partners to create nested Magneto-FISH enrichments from methane seep sediment incubations under methane headspace. This method allows us to examine potential physical associations between ANME and SRB taxa and other microorganisms using co-occurrence statistical methods applied to iTag sequences from nested Magneto-FISH enrichments.
ANME have been broadly divided into three separate groups, which can be further subdivided into ANME-1a, 1b, 2a, 2b, 2c, and 2d, and 3. ANME-1 archaea are a unique order-level lineage within the Euryarchaeota, between the Methanomicrobiales and the Methanosarcinales, known to associate with sulfate-reducing bacteria, but obligately associated lineages have yet to be defined. ANME-2 archaea, within the order Methanosarcinales, commonly form associations with Desulfosarcina/ Desulfococcus-related (DSS) sulfate-reducing Deltaproteobacteria (;; ). They have also been found in association with Desulfobulbus-related (DSB) Deltaproteobacteria in the same environments, where geochemical factors have been suggested as a possible explanation for partner differentiation. ANME-2a/b and ANME-2c both predominately associate with a subgroup of DSS, SEEP-SRB1 , but also form consortia with DSB (; ).
ANME-3 has been found in association with Desulfobulbus-related Deltaproteobacteria and SEEP-SRB1. These ANME groups have also been observed in the environment without bacterial partners (;;; ). In addition to ANME archaea, other uncultured archaeal lineages commonly recovered from methane seeps include Marine Benthic Group-D ( Thermoplasmatales), Deep Sea Archaeal Group/Marine Benthic Group-B (; ), and sometimes methanogens (;;; ). Deltaproteobacteria diversity beyond DSS and DSB has also been well described in methane seeps.
In addition to SEEP-SRB1, define three more Deltaproteobacteria clades within Desulfobulbaceae (SEEP-SRB2, 3 and 4). Also described a Desulfobulbaceae affiliated seepDBB group in methane seep systems. Bacterial diversity surveys of methane seep habitats frequently report occurrence of other diverse Proteobacteria including sulfur oxidizers ( Gammaproteobacteria and Epsilonproteobacteria) and putative heterotrophs ( Alphaproteobacteria and Betaproteobacteria) (; ).
Many other bacterial phyla have also been found such as Firmicutes, Thermomicrobia, Bacteroidetes, Chlorobi, Nitrospira, WS3, OD1, OP11, TM7, and WS6 ; Cytophaga and Flavobacteria ; Chloroflexi, Atribacteria (previously Candidate Division JS1), CD12, WS1, OS-K, AC1, and Planctomycetes ; and Acidobacteria. Identified Methanomicrobia, Deltaproteobacteria, Hyd24-12 and Atribacteria (JS1) as the characteristic ‘core’ microbial taxa in methane seep ecosystems, as compared to Gammaproteobacteria, Flavobacteria, Thermoplasmatales, and MBG-B taxa that were found in high relative abundance in seeps and other marine ecosystems. Despite the wealth of bacterial and archaeal diversity in methane seep sediments, little is known about potential associations with ANME/SRB, or associations that do not involve ANME or SRB. Our study utilizes the novel combination of targeted Magneto-FISH enrichment of specific microbial taxonomic groups and iTag sequencing to develop statistically supported co-occurrence microbial networks to address knowledge gaps in our understanding of methane seep microbial communities.
Network analysis revealed many novel associations between methane seep Proteobacteria taxa and Candidate phyla. The significant co-occurrence observed by these OTUs suggests new avenues for future studies on microbial interactions involved in carbon and sulfur cycling in methane seep systems. Materials & Methods Sample collection and Magneto-FISH iTag Magneto-FISH enrichments were conducted using a large scale (1 L) incubation of methane seep sediment from Hydrate Ridge North (offshore Oregon, USA) collected in September 2011 at 44°40.0 2 ′ N 125°6.0 0 ′ W, from a water depth of 775 m using the ROV JASON II and the R/V Atlantis. Marine sediment was collected using a push core to sample a sulfide-oxidizing microbial mat adjacent to an actively bubbling methane vent. A sediment slurry from the upper 0–15 cm depth horizon of the push core was prepared with 1 volume N 2 sparged artificial seawater to 1 volume sediment, overpressurized with methane (3 bar) and incubated at 8 °C in a 1 L Pyrex bottle capped with a butyl rubber stopper until subsampling for Magneto-FISH. In February 2015, incubation samples were immediately fixed in 0.5 ml sediment aliquots in 2% paraformaldehyde (PFA) for 3 h at 4 °C.
The samples were washed in 50% phosphate-buffered saline (PBS): 50% EtOH, then 75% EtOH: 25% DI water, and resuspended in 2 volumes (1 ml) 100% ethanol. Samples were centrifuged at 1,000 × g for 1 min between wash steps. After fixation, the Magneto-FISH method first described by and further optimized by and was used.
Briefly, a liquid CARD-FISH reaction was followed by immunomagnetic bead incubation coupled with anti-fluorescein attaching magnetic beads to CARD-FISH hybridized aggregates. Samples were then held against magnets and the sediment matrix was washed away, retaining target cells and physically associated microbes in the magnetic portion as described in. Four previously published FISH probes were used targeting a range of Deltaproteobacteria and Methanomicrobia. A subset of three 0.5 ml aliquots was also immediately frozen before fixation (unfixed bulk sediment), and another three aliquots were frozen after fixation (fixed bulk sediment) for bulk sediment comparison with Magneto-FISH enrichments. Sediment for MSMX-Eel932 Magneto-FISH metabolic gene analysis was fixed and washed onboard in September 2011, as described above.
See methods flow chart provided in. DOI: iTag amplification For iTag sequencing, ten Magneto-FISH enrichments were performed in parallel using the FISH probes DSS658 (triplicate), MSMX-Eel932 (triplicate), SEEP-1a1441 (duplicate), Delta495a + Delta495a competitor (duplicate).
Magneto-FISH enrichments and bulk sediment samples were resuspended in 650 µl solution PM1 and transferred to silica tubes from the PowerMicrobiome RNA Isolation Kit (MoBio). This kit was chosen based on manufacturer recommendation for formalin-fixed sediment samples, with the added capability to co-elute RNA if desired. 6.5 µl of beta-mercaptethanol was added, and samples were mechanically lysed in a bead beater (FastPrepFP120; Thermo Electron Corp., Waltham, MA, USA) for 45 s at setting 5.5 and incubated at 65 °C for 3.5 h. The remaining steps in the PowerMicrobiome RNA Isolation Kit were followed according to manufacturer instructions (starting at step 5) without any DNase procedures, and eluting in a final volume of 60 µl ultrapure water. DNA extracts were quantified using a Qubit Flurometer and HS dsDNA kit (Invitrogen; ). All but one Magneto-FISH sample had DNA concentrations below detection (.
16S rRNA gene iTag and clone library relative sequence abundance for seep microbiome OTUs. Relative sequence abundances were computed for the top 135 OTUs in the iTag dataset.
These OTUs correspond to ∼55% of the total sequences in the unfixed bulk sediment. Bacterial and archaeal 16S rRNA gene libraries are included for the core methane seep taxa, with the total number of clones for each library indicated above. Core methane seep taxa were based on and include: candidate Phylum Atribacteria, Candidate Division Hyd24-12, Methanomicrobia, Caldilineales, Desulfobacterales, and Spirochaetales. While we did recover other Chloroflexi, no Caldilineales were recovered in iTag or gene library sequencing so they are not included below. Fixed bulk sediment was chosen for baseline comparison (rather than unfixed) since it includes the potential loss of cells due to fixation and wash steps, thereby processed more similarly to the Magneto-FISH samples.
An average and standard deviation for relative sequence abundance among replicates was calculated for each sample set. A ratio of the average relative sequence abundance of Magneto-FISH enrichments compared to the fixed bulk sediment value is reported (Rel. Ratios over 1.5 are underlined. 16S rRNA gene bacteria and archaea clone libraries for two Magneto-FISH enrichments and fixed bulk sediment are also included for comparison to recovered iTag diversity. 16S rRNA gene (iTAG) 16S rRNA gene (Clone Library) Seep1a1441 DSS658 Delta495a MSMX-Eel932 Fixed bulk Unfixed bulk DSS658 MSMX-Eel932 Fixed bulk Taxon Avg.
24 arc, 41 bac Rel. Fixed 60 arc, 87 bac Rel. DOI: iTag samples were prepared with Earth Microbiome Project (EMP) primers 515f and 806r. An initial amplification of 30 cycles with primers lacking the barcode, linker, pad, and adapter was performed for all samples, in duplicate.
Duplicate PCR reactions were pooled and reconditioned for 5 cycles with barcoded primers, for a total of 35 cycles. A master mix of 2 X Q5 Hot Start High Fidelity Master Mix (NEB) and 10 µM forward and reverse primers was prepared for a final volume of 15 µl per sample, with 1 µl DNA template. PCRs had an initial 2 min heating step at 98 °C, followed by cycles of 10 s 98 °C, 20 s 54 °C, and 20 s 72 °C, and finished with a final extension of 2 min at 72 °C. PCR negative controls, substituting ultrapure water for DNA template, were amplified for 40 cycles total. We note that these are not the official recommended reagents or PCR conditions from the EMP, but internal lab tests showed that for 6 out of 9 mock community taxa, recovered sequence relative abundances were more accurate when using Q5 polymerase rather than the recommended Hot Start MasterMix (5-prime). EMP primers were chosen for iTag for cross-comparison between studies, though there is known primer bias within this universal primer set and sequencing reactions will always have some inherent variability.
Mock communities Four mock communities were prepared with a range of relative proportions of nine common methane seep taxa. Full-length 16S rRNA gene plasmids from each taxa listed were quantified by Qubit. Taking into account the plasmid’s nucleotide composition and length in order to calculate its molecular weight, plasmids were quantitatively combined in known volumetric fractions to achieve a range of desired mock community compositions. These combined plasmid mixes were diluted to ∼1 ng/µL and then prepared according to the same iTag methods as all other samples. ITag sequence processing We followed the mothur Standard Operating Procedure (SOP) for Illumina MiSeq sequencing of the 16S rRNA gene V4 region, accessed May 2015 and using methods described in with UCHIME chimera checking. A concatenated file of the mothur version of separate archaeal and bacterial SILVA 119 databases was used for alignment and classification.
Unfixed Bulk Sediment 1 only returned 8% of the average DNA concentration of the other two samples. This sample was removed from statistical analyses because it fails to be a representative of the unfixed bulk sediment community baseline. The mock communities were processed following the “Assessing Error Rates” section of the mothur SOP to compute sequencing error rates and spurious OTU rates. Additional analysis demonstrating sequence processing did not selectively remove ANME-2c sequences and relative sequence abundances recovered with iTag sequencing of mock communities are provided in and, respectively. Using R version 3.1.3 , an average number of sequences per OTU was calculated from unfixed bulk sediment samples (2 and 3).
All OTUs with an average relative sequence abundance below 0.1% in the unfixed bulk sediment were identified and removed from all samples using mothur. 135 unique OTUs remained out of 25,354. We also verified that after the 0.1% cutoff was applied, no negative control contaminant OTUs remained. The top 20 OTUs amplified from the no template negative control were classified as, in order of sequence abundance: Sphingomonas.; Planctomyces.; Escherichia-Shigella.; Staphylococcus; Roseomonas.; Pir4 lineage; Delftia.; Macrococcus; Myxococcales;0319-6G20;unclassified; Planctomyces; Enhydrobacter; Sphingobium.; Caenispirillum; Bacillus.; Pseudoxanthomonas.; Peptoniphilus; Lysobacter; Salinicoccus; Propionibacterium. Reagent contaminant genera discussed in are denoted by (.).
All samples (including mock community and negative controls) were submitted to the SRA under the accession, BioSample:, Sample name: PC47 (5133-5137) mixed slurry. Gene libraries of the Magneto-FISH samples were prepared as in using the primers and annealing temperatures listed in and TOPO TA Cloning Kit for Sequencing with pCR4-TOPO Vector and One Shot Top 10 chemically competent Escherichia coli (Life Technologies). All full-length 16S rRNA gene sequences were aligned by the SINA online aligner ( v1.2.11) and added using maximum parsimony to the SILVA 119 database for classification. A taxonomy-based count table was prepared (sequences per taxa, per sample) and all taxa absent from the bulk sediment library were removed from Magneto-FISH enrichment libraries (for parity with iTag contaminant removal processing). Functional gene sequences were translated using the EMBOSS online translation tool , then added to ARB databases for phylogenetic placement and classification. Sequences were submitted to NCBI under the following accession numbers: AprA ( – ), DsrA ( – ), McrA ( – ), Archaeal 16S rRNA gene ( – ), Bacterial 16S rRNA gene ( – ), SoxB ( – ). Gene trees were computed with representative sequences using PhyML 3.0 online execution with defaults on the South of France Bioinformatics platform.
Statistical analysis Weighted UniFrac , Metastats , and linear discriminant analysis (LDA) effect size (LEfSe) analyses were computed in mothur as outlined in the mothur SOP. Co-occurrence statistical analyses were run using the table of 135 unique OTUs in the format of sequence counts of each OTU per sample. The program SparCC was used to determine significant correlations. This analysis was run 100 times with default settings, except 10 iterations were used instead of 20.
OTUs with SparCC correlations above an absolute value of 0.6 with p-values below 0.01 were considered significant. Resulting associations that occurred in at least 50 out of 100 network iterations are provided in.
Cytoscape was used to display associations in. Figure 1: Network diagram of Magneto-FISH and bulk sediment samples.
Co-occurrence analysis of the top 135 unique OTUs displayed in network form. Nodes represent the taxonomy of the OTUs in the network and edges are the connections between OTUs. Node size is scaled by number of connecting OTUs and colored by simplified, putative metabolic guild (sulfate reducer: blue, small dash; sulfur oxidizer: yellow, medium dash; archaeal methanotroph: magneta, large dash; mixotroph: green, no dash; heterotroph: brown, no outline). Edge thickness is scaled by number of occurrences of this association (from 50 to 100 times) and number of occurrences also included along edge.
Negative associations are denoted by hashed lines. The combined network is displayed using Cytoscape, with the average correlation coefficient across all runs determining the distance between nodes and the number of occurrences in 100 network iterations determining edge width. DOI: CARD-FISH microscopy A triple CARD-FISH hybridization was performed with bacterial probes listed in, ANME-1350 and MSMX-Eel932. The sample preparation and CARD reaction was performed as per.
After the three CARD reactions, samples were post-stained with DAPI (25 ng/µl). CARD signal within any part of a physically attached group of cells larger than 10 µm was counted as a positive identification. For example, a large EPS matrix that contained many smaller separate ANME-1 and ANME-2 aggregates would count as one positive identification for each clade. This was done to simulate groups that would have been isolated together in a Magneto-FISH enrichment.
Since the MSMX-Eel932 probe also targets the ANME-1 population, only cells with MSMX-Eel932 signal and no ANME-1350 signal were recorded as an ANME-2 positive identification to comprehensively target ANME-1, -2, and a bacterial partner in a triple CARD-FISH hybridization set. ANME-3 were not recovered in the iTag dataset and were not considered as potential contributors to MSMX-Eel932 signal. Results Relative sequence abundance of seep microbiome taxa in 16S rRNA gene iTag and libraries Relative sequence abundances of the methane seep microbiome characteristic taxa, ANME archaea, Deltaproteobacteria, Hyd24-12, and Atribacteria , were compared two ways: (1) between iTag and gene library 16S rRNA gene samples to determine how relative sequence abundances differed between sequencing methodologies, and (2) between Magneto-FISH enrichment and bulk sediment to determine taxa-specific relative sequence abundance for each probe. Mock community analysis showed that ANME-2 were always underrepresented in iTag data (0.32–0.81 fold of what was expected), whereas the Deltaproteobacteria and ANME-1b were more faithfully represented. ANME-1a was consistently overamplified.
By normalizing the relative sequence abundance of ANME-2c, -2a/b, and -1a to the abundance of ANME-1b, the most faithfully amplified archaea in the mock community data , we could compute a ratio between the average relative sequence abundance in fixed bulk sediment samples between iTag and the archaeal 16S rRNA gene library. ANME-2c (0.04 iTag:clone ratio), ANME-2a/b (0.12), and ANME-1a (0.40) were all less abundant in iTag sequences as compared to the archaeal gene library (calculated from values in ). Similarly comparing SEEP-SRB1 to Desulfobulbus between the two methods in fixed bulk sediment returns a ratio of 0.41 iTag:clone. Since the iTag methodology recovers far more diversity (e.g., Desulfobacula, Desulfocapsa, Desulfoluna, Atribacteria, and Hyd24-12 were not recovered in the bacterial 16S rRNA gene bulk sediment library), it is expected that the relative sequence abundances of each individual taxon computed from iTag data would be less than the domain targeted 16S rRNA gene libraries. However the ANME-2c abundance ratio was an order of magnitude less than ANME-1a and SEEP-SRB1 ratios, and appears to be an extreme case of underestimation in iTag data. There was also variation between Magneto-FISH enrichment replicates, as indicated by the high standard deviations of Magneto-FISH samples as compared to bulk sediment samples. The degree of variation (average standard deviation across all taxa listed) correlated with the specificity of the probe; where Delta495a had the lowest average standard deviation and Seep-1a1441 had the highest average standard deviation.
The high relative sequence abundance taxa (1.5 fold relative sequence abundance increase over fixed bulk sediment; ) in the averaged Seep-1a1441 iTag Magneto-FISH enrichments were Desulfoluna (2.20), SEEP-SRB1 (2.36), Hyd24-12 (3.44) and Atribacteria (1.51). The DSS658 enrichment had fewer high relative sequence abundance taxa with only Desulfoluna (4.62), Spirochaeta (4.36), and Atribacteria (4.80). The Delta495a enrichment also had three high relative sequence abundance taxa with Desulfobulbus (2.52), Spirochaetae-uncultured (3.70), and Atribacteria (3.02). The MSMX-Eel932 enrichment had six high relative sequence abundance taxa with Desulfococcus (1.85), Desulfoluna (8.47), SEEP-SRB1 (1.67), Spirochaeta (1.63), Hyd24-12 (1.73), and Atribacteria (7.18).
Gene library results showed high relative sequence abundance (1.5) in both ANME and Deltaproteobacteria with DSS658 and MSMX-Eel932 enrichments. Similar to the bulk sediment, Desulfobacula, Desulfocapsa, Desulfoluna, Atribacteria and Hyd24-12 were not recovered in the bacterial 16S rRNA gene Magneto-FISH libraries. MSMX-Eel932 enriched for SEEP-SRB1 (2.73), SEEP-SRB4 (3.28), Desulfococcus (3.82), Spirochaeta (1.64), and ANME-2a/b (2.51) in 16S rRNA gene libraries. There was also a slight enrichment of ANME-2c (1.28). The DSS658 enrichment had high relative sequence abundance for SEEP-SRB1 (1.74), SEEP-SRB2 (2.78), ANME-2c (1.54), and ANME-2a/b (2.24) with iTag, but these same taxa did not have high relative sequence abundance in the gene library. Spirochaeta and SEEP-SRB1 had high relative sequence abundance in both iTag and gene libraries for MSMX-Eel932 enrichments. Relative sequence abundances for all non-core methane seep taxa in iTag samples are included in, and where Magneto-FISH enrichments of these additional taxa support network co-occurrences they are discussed in network results.
ITag relative abundance of remaining ‘non-core’ methane seep microbiome OTUs. Relative sequence abundances were computed for the top 135 OTUs in the iTag dataset that were not included in the core methane seep microbiome. An average and standard deviation for relative sequence abundance among replicates was calculated for each sample set. A ratio of the average relative sequence abundance of Magneto-FISH enrichments compared to the fixed bulk sediment value is reported (Rel.
Ratios over 1.5 are underlined. 16S rRNA gene bacteria and archaea clone libraries for two Magneto-FISH enrichments and fixed bulk sediment are also included for comparison to iTag enrichment. Seep1a1441 DSS658 Delta495a MSMX-Eel932 Fixed bulk Taxon Avg. DOI: Statistical evaluation of Magneto-FISH enrichment To statistically compare enrichment microbial communities, we used a suite of statistical tests including: non-parametric T-tests , LEfSe , and UniFrac. Using the T-test comparison, ten OTUs were significantly ( p.
DOI: Assessing community structure with co-occurrence network analysis After determination of statistically significant differences between iTag Magneto-FISH and bulk sediment samples, we computed co-occurrence networks to observe which of the 135 most abundant OTUs were correlated in the methane seep microbial community. By combining the results from 100 separate microbial association calculations, we were able to assign confidence to each microbial association and determine the most robust associations.
Significant associations are reported in and depicted as a network in. Focusing first on the common ANME syntrophic Deltaproteobacteria partner, SEEP-SRB1, this taxon had the most associations in the network including nine positive associations and one negative association. There are two separate sets of SEEP-SRB1 & Planctomycetes (AKAU3564 sediment group) positive associations that are both well supported. SEEP-SRB1 is also associated with three other heterotrophic taxa (Candidate Phylum Atribacteria, Spirochaeta, and Bacteroidetes (VC2.1 Bac22)) and one sulfur-oxidizing taxa ( Sulfurovum). SEEP-SRB1 was also associated with Candidate Division Hyd24-12, which has a currently unknown ecophysiology, but could be a heterotroph if the topology of heterotrophic taxa being in the center of the network holds true.
Hyd24-12 and Atribacteria are also both associated with the second most associated taxa, Candidate Division OD1, but there was no direct association between SEEP-SRB1 and OD1. SEEP-SRB2 has two of the same associations as SEEP-SRB1 (VC2.1Bac22 and Atribacteria), but is the only Deltaproteobacteria associated with MBG-B, Anaerolineaceae, and Desulfoluna (another Deltaproteobacteria). SEEP-SRB4 is associated with Desulfobulbus, and the only Deltaproteobacteria associated with and ANME (2a/b), WS3, and Actibacter. WS3 had high relative sequence abundance in both DSS658 and MSMX-Eel932 enrichments.
Desulfobulbus is associated with Desulfococcus, the only Deltaproteobacteria associated with BD2-2, and SAR406. SAR406 had high relative sequence abundance in Seep1a1441 and Delta495a enrichments. The heterotroph Spirochaeta is also included in the core methane seep microbiome and was associated with Clostridia and WS3, in addition to Hyd24-12 and SEEP-SRB1. In examination of additional OTUs associated with sulfur metabolisms, we found Sulfurovum and Sulfurimonas ( Epsilonproteobacteria) were not associated with each other, but are both associated with Deltaproteobacteria. Sulfurimonas is associated with Desulfocapsa and Sulfurovum is associated with SEEP-SRB1 and Desulfobulbus. Sulfurovum had high relative sequence abundance in MSMX-Eel932 enrichments and Sulfurimonas had high relative sequence abundance in Seep-1a1441, DSS658, and Delta495a enrichments. The Gammaproteobacteria, Thiohalobacter, is only associated with Anaerolineaceae and was not elevated in any of the Magneto-FISH enrichments.
Heterotrophs are the most dominant metabolic guild in the network, and similar to sulfate-reducers, have some of the most connected taxa. The heterotroph OD1 has seven positive correlations, in addition to Atribacteria and Hyd24-12 listed above: Bacteroidetes (BD2-2), Actinobacteria (OM1), Pelobacter, ANME-1b, Chloroflexi ( Anaerolineaceae), and Desulfocapsa. Anaerolineaceae and Bacteroidetes (BD2-2) both had seven associations, but with different connectivity. BD2-2 was interconnected with other heterotrophs, sulfate-reducers, and archaeal methanotrophs in the main portion of the network, whereas Anaerolineaceae was connected to three taxa that share no other connections (two heterotrophs and one Gammaproteobacteria sulfur oxidizer). The one other ANME taxa in the network, ANME-1b, is only positively associated with heterotrophs and no known sulfate reducing groups. Assessing ANME-bacterial partnerships by CARD-FISH To assess ANME and DSS relative cell abundance, 100 aggregate clusters from the same sediment incubation (see ‘Materials & Methods’) were analyzed with CARD-FISH and the DSS658/ANME1-350/MSMX-Eel932 probe combination.
Epsi404, Gam42a, SEEP-1a1441, and CF319A/B probes were also used with the archaeal probe combination to examine non-DSS bacterial diversity recovered in the network analysis ANME associations. All probes, target populations, and references are listed in.
30% of aggregates contained an ANME-2 signal (see ‘Materials & Methods’; ) and 39% of aggregates had an ANME-1 signal. ANME-1 and ANME-2 identified cells were also consistent with expected morphologies. Multiple clusters of mixed-type ANME/DSS, DSS-only, ANME-only, DSS/non-ANME, and non-DSS/non-ANME aggregates were observed with the ANME-1350, MSMX-Eel932, and DSS658 probe combination.
There were no clear examples of aggregates with ANME/non-DSS hybridized cells, though we found many instances where both ANME and non-DSS cells were as part of a larger aggregate cluster with other cell types. ANME-1 cells often occurred in the matrix surrounding tightly clustered ANME-2 aggregates. The SEEP-1a1441 probe, targeting a subgroup of DSS, was observed to hybridize with aggregate clusters that contained ANME-1 and ANME-2 cells, but usually with SEEP-SRB1/ANME-2 in tight association and ANME-1 in more peripheral association.
Five of the SEEP-SRB1/ANME-2 aggregate clusters did not have ANME-1 cells (10%) and three of the SEEP-SRB1/ANME-1 aggregate clusters did not have ANME-2 cells. Significance of relationship between communities is reported with p-values: ∗. Mock sediment community sequence recovery Expected and recovered sequence abundances among the mock communities show differential taxonomic biases. Fold Change is calculated by dividing the experimentally recovered relative abundance by the expected relative abundance. Four mock communities were designed with a selection of common methane seep bacterial and archaeal taxa at different relative abundance ratios.
Mock community analysis revealed that relative abundances of Helicobacteraceae ( Sulfurovum), Desulfobacteraceae (Seep-SRB1) and Desulfobulbaceae ( Desulfobulbus) had little amplification bias as compared to other mock community taxa (fold change ranges 0.93–1.42, where 1.00 means expected relative abundance was returned). ANME-1b plasmids were also overall well represented (fold change 0.64 to 1.42) across the range of expected relative abundances (1% to 20%). In contrast, ANME-2a/b and ANME-2c plasmids were always under amplified in all of the mock communities (fold change 0.32 to 0.81). These results do not appear to correlate to primer hits in the SILVA SSU r123 database, where 89.5% of ANME-2c sequences were hit by 515f and 87.1% by 806r, but 94.3% of ANME-2a/b were hit by 515f and 806r. ANME-2a/b was a better match to the EMP primers, but both taxa were under amplified in mock community analysis. Amplification bias was not always uniform, where some templates saw varied amplification response depending on initial relative abundance in the mock community.
The ANME-1a plasmid was over-amplified (3.35–2.44 fold change; ) when the plasmid was at 5% relative abundance and lower (Mock Communities 1–3). However, Mock Community 4 with the highest relative abundance (20%) of ANME-1a plasmids, saw templates amplified to the expected relative abundance (0.97 fold change). Thaumarchaeota: miscellaneous Crenarchaeota Group followed a similar pattern to ANME-1a: where it was 1% expected relative abundance, the fold change is ∼5, and where it was 10% expected relative abundance, the fold change was less pronounced (∼1.5). MBG-D sequences were slightly over amplified when at 1% expected relative abundance, and slightly under amplified when at 42% relative abundance. Bias was consistent across mock community samples when the relative percentage of that group (e.g., Thermoplasmatales, 40%) was the same in both samples.
This suggests that analysis based on relative abundance between samples can be applied as a means of comparison, as long as the environmental OTUs of interest are above the detection threshold. A study of EMP primers with a pelagic marine community also reported discrepancies between mock community bias and independently assessed environmental sample bias for a dominant community members (Parada et al., 2015). Parada et al. Similarly conclude that over-amplification of certain community members, in their case Gammaproteobacteria, was the cause of lower than expected recovery, rather than lack of SAR11 and SAR116. Our ANME-2c results, therefore, serve as yet another example of how key community members can be under-represented when exploring unknown microbial systems.
The severity of this issue for future studies is dependent on the research question, interpretation approach, and the phylogenic bias imparted on community members of interest. The phenomenon of less pronounced bias when templates are at higher starting relative abundances could be explained by the reannealing inhibition affect of high copy number templates in mock samples (Suzuki & Giovannoni, 1996). Due to low template of Magneto-FISH samples, PCRs were done for a total of 35 cycles. Since bias is positively correlated with number of cycles (Suzuki & Giovannoni, 1996), lowering PCR amplification cycles could improve bias issues. The lack of statistically significant ANME-2c correlations is expected since this group was recovered in so few samples. ANME-1a, however, may suffer from the opposite problem where over-amplification in iTag datasets reduces the ability to determine patterns with other OTUs. As an analogy, if the ANME-2c population is an image with only a few pixels and the image of the ANME-1a population is an image with oversaturated pixels, then neither has a workable dynamic range for correlation analysis.
The log transform operation performed on the data before correlation analysis can reduce the bias between high and low abundance OTUs to some degree, but may not be sufficient in all cases, such as with these two OTUs. Sequences per sample post processing Total sequences per sample after mothur processing and 0.1% bulk sediment cutoff and total sequences remaining for the most abundant ANME-2c, SEEP-SRB1, and ANME-1a OTUs. We also performed a BLASTN (Maddenm 2002) search of all contigs from all samples against an in-house database of 155 ANME-2c 16S rRNA sequences of 500 bp.
This yielded 1,395 iTag sequences with an e-value greater than or equal to 10 −130, corresponding to 99–100% sequence identity match to sequences from our ANME-2c database. We then tracked this set of BLAST match contigs through each step in the mothur pipeline, with a final result of 1,260 sequences remaining in this BLAST set from the original contig file. Thus 92% of our ANME-2c BLAST hit set remained through the mothur processing pipeline. This suggests that the lack of ANME-2c sequences in our downstream database was not due to spurious removal during sequence processing. Mock community sequencing error rates Mock Community sequencing error rates (0.025–0.095%; ) were of the same magnitude as Kozich et al. (∼0.01%, 2013). Rarefaction of the mock community to 5,000 sequences shows OTU inflation rates of 3 to 4 times expected number of OTUs, after 97% OTU clustering and removal of singletons.
Full Cast And Crew
The inflation rate is calculated by total number of OTUs recovered divided by original number of template plasmids. Since our environmental mock community only had 12 templates, the number of spurious OTUs is expected to be high (Huse et al., 2010). Experimental sediment samples have 10 to 100 times more templates, so inflation rates are expected to be much lower (10–1%). The following information was supplied regarding data availability: GenBank sequences: AprA ( – ), DsrA ( – ), McrA ( – ), Archaeal 16S rRNA ( – ), Bacterial 16S rRNA ( – ), SoxB ( – ) SRA: accession, BioSample:, Sample name: PC47 (5133–5137) mixed slurry. Funding This research is funded by the Department of Energy, Office of Science, Office of Biological and Environmental Research (DE-SC0003940) and the Gordon and Betty Moore Foundation through Grant GBMF 3780 (both to VJO).
Matrix 1999 Turkce Dublaj Film Izle
ETR was supported by a NIH/NRSA Training Grant (5 T32 GM07616). Funding for DHC was provided in part by an NSF Graduate Research Fellowship. Samples were collected with funding from the National Science Foundation (BIO-OCE 0825791; to VJO). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. References.