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Keywords:

  • amplicon length heterogeneity;
  • methanogenic Archaea;
  • methyl-coenzyme M reductase

Abstract

  1. Top of page
  2. Abstract
  3. Introduction
  4. Materials and methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References
  9. Supporting Information

Understanding the ecology of methanogens in natural and engineered environments is a prerequisite to predicting or managing methane emissions. In this study, a novel high-throughput fingerprint method was developed for determining methanogen diversity and relative abundance within environmental samples. The method described here, designated amplicon length heterogeneity PCR of the mcrA gene (LH-mcrA), is based on the natural length variation in the mcrA gene. The mcrA gene encodes the alpha-subunit of the methyl-coenzyme M reductase, which is involved in the terminal step of methane production by methanogens. The methanogenic communities from stored swine and dairy manures were distinct from each other. To validate the method, methanogenic communities in a plug flow-type bioreactor (PFBR) treating swine manure were characterized using LH-mcrA method and correlated to mcrA gene clone libraries. The diversity and relative abundance of the methanogenic groups were assessed. Methanobrevibacter, Methanosarcinaceae, Methanoculleus, Methanogenium, Methanocorpusculum and one unidentified group were assigned to particular LH-mcrA amplicons. Particular phylotypes related to Methanoculleus were predominant in the last compartment of the PFBR where the bulk of methane was produced. LH-mcrA method was found to be a reliable, fast and cost-effective alternative for diversity assessment of methanogenic communities in microbial systems.


Introduction

  1. Top of page
  2. Abstract
  3. Introduction
  4. Materials and methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References
  9. Supporting Information

Methanogenesis is a microbiological process of major environmental and industrial interest. Methane is, with CO2 and N2O, a major contributor to global warming (IPCC, 1996). On the other hand, methane produced from anaerobic digestion of organic wastes in engineered systems is a source of renewable energy (Lettinga, 1995). Therefore, it is important to improve our understanding of the ecology of bacteria and Archaea that together catalyse methanogenesis.

Methanogenesis is carried out by complex anaerobic consortia of fermentative bacteria and methanogenic Archaea, or methanogens. Communities of hydrolytic, acidogenic and acetogenic bacteria ferment the macromolecules into acetate and/or H2 (or formate) + CO2. The direct conversion of H2 (or formate) + CO2 to methane is catalysed by hydrogenotrophic methanogens. The acetate conversion to methane and CO2 can be performed through two alternative pathways. The first pathway, catalysed by acetoclastic methanogens (species of Methanosarcina or Methanosaeta), is a cleavage of the methyl and carboxyl groups from acetate producing methane and CO2, respectively. The second possible pathway relies on the syntrophic association between acetate oxidizing bacteria and hydrogenotrophic methanogens: the formers convert acetate into H2 and CO2, which are then used by the hydrogenotrophic methanogens to produce methane (Schink & Stams, 2006). Regardless of the environmental conditions and of the predominance of either acetoclastic or hydrogenotrophic pathways, methanogenic Archaea, as the terminal oxidizers of the community, play a key role. As a consequence, developing new and rapid methods to elucidate the identity and diversity of methanogens would be useful for the global understanding of the complex process of methanogenesis.

The methyl-coenzyme-M reductase enzyme complex (MCR), composed of two alpha, beta and gamma subunits, catalyses methane formation and is ubiquitous in methanogens (Thauer, 1998). MCR is unique to methanogens, with the exception of the methane-oxidizing Archaea (Hallam et al., 2003). In addition, a few members of the Methanomicrobiales and Methanococcales also possess a type II isoenzyme (Mrt) (Lehmacher & Klenk, 1994). On the basis of the comparison of available 16S rRNA and mcrA gene sequences of methanogens, the mcrA gene was demonstrated to be an alternative phylogenetic marker to the 16S rRNA gene (Luton et al., 2002). T-RFLP fingerprints of the mcrA gene have been used for phylogenetic analysis of methanogen populations (Lueders et al., 2001). Our objective in this study was to develop a novel fingerprinting method that distinguishes the methanogenic groups from environmental or engineered systems that should be less time-consuming, more cost-effective, but as informative as T-RFLP. This methodology, based on the natural length variations of the mcrA gene, originates from the work of Suzuki et al. (1998), who developed the amplicon length heterogeneity PCR method (LH-PCR) based on the natural length variation of the bacterial 16S rRNA gene. In this study, the new methodology we have developed and named amplicon LH-PCR of the mcrA gene (LH-mcrA) is validated using clones from libraries from a plug flow-type bioreactor (PFBR).

Materials and methods

  1. Top of page
  2. Abstract
  3. Introduction
  4. Materials and methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References
  9. Supporting Information

Environmental samples

The PFBR consisting in eight serially linked compartments was operated at 25 °C and fed with liquid swine manure at a rate of 1–2 g chemical oxygen demand (COD) L−1 day−1 and a hydraulic retention time of 60 days, as described in Roy et al. (2009). Samples from the first and the last compartments (PF1 and PF8, respectively) of the PFBR were obtained after 6 months of operation (at steady state) as described previously (Roy et al., 2009). Hydrolysis and acidogenesis stages occurred in the first compartments, whereas the final methanogenesis stage occurred in the last compartments (Roy et al., 2009).

Dairy and swine manure samples were obtained from the bottom sediments of outdoor concrete manure storage tanks on an intensive swine operation and a dairy cow farm located near Sherbrooke, QC, Canada. One litre samples of manure slurry (turbid liquid with particles) were obtained using a sampler consisting of a 12-foot-long aluminium rod connected to a container with a retractable lid. Following collection, the manure slurry was homogenized by manual mixing, and triplicate samples (0.5 mL) were frozen in liquid nitrogen and stored at −80 °C.

DNA extraction and LH-mcrA fingerprints

DNA was recovered from the frozen samples using a previously described method (Griffiths et al., 2000) with minor modifications described in Roy et al. (2009). PCR amplicons were produced using a primer set based on the previously described ML primer set (Luton et al., 2002) but modified to improve coverage by including additional degeneracies and truncating the forward primer: (1) primer mcrAfornew: 5′-GGTGTMGGDTTCACHCARTAYGC-3′ and (2) primer mcrArevnew: 5′-TTCATNGCRTAGTTHGGRTAGTT-3′). PCR amplification, LH-mcrA migration on a capillary DNA genetic analyzer (ABI Prism 310; Applied Biosystems, Steetsville, ON, Canada) and fingerprint analysis were carried out as described for LH-PCR (Talbot et al., 2009). In brief, the annealing temperature was 55 °C, but the final extension step was shorten to 10 min. The reproducibility of LH-mcrA results was determined by comparing the standard deviation (SD) of the amplicon lengths and the relative abundances of the different peaks.

Construction of mcrA gene clone libraries

Two clone libraries were constructed from DNA extracted from PF1 and PF8 of the PFBR (Roy et al., 2009). Amplicons were produced with the newly designed mcrA gene primers (see above). DNA templates (100 ng) were incorporated into the 50 μL PCR mixture composed of 1× PCR buffer containing MgCl2 (GE Healthcare Bio-Sciences Inc., Baie d'Urfe, QC, Canada), 0.5 μM of each primer, 0.2 mM of dNTP (Amersham, GE Bio-Sciences Inc.) and 1.25 U of Taq DNA polymerase (GE Healthcare Bio-Sciences Inc.). The reaction mixture was initially denatured at 94 °C for 5 min, followed by 28 cycles of 94 °C for 60 s, annealing at 52 °C for 60 s and elongation at 72 °C for 90 s, with a final extension step at 72 °C for 7 min. PCR products were purified with the QIA quick PCR purification kit (Qiagen Inc., Mississauga, ON, Canada). Purified amplicons were ligated into pCRII vector using the TA cloning kit (Invitrogen Canada Inc., Burlington, ON, Canada) containing One Shot Escherichia coli Top10F’ cells, following manufacturer's instructions. Transformants were selected by picking white colonies on LB-Ampicillin plates containing Bluo-Gal (Invitrogen Canada Inc.) and IPTG, followed by an overnight cultivation in liquid LB-ampicillin medium. Plasmids were extracted using the QIAprep spin mini prep kit (Qiagen Inc.) for sequencing.

DNA sequencing

Plasmid DNA sequencing reactions were carried out using the BigDye Terminator v3.1 cycle sequencing kit and run on an ABI 3130 genetic analyzer (Applied Biosystems, Foster City, CA) using a 36-cm capillary column containing POP7 polymer. mcrA clones were sequenced from each end using the M13 forward and reverse primers. Fragments were aligned using Sequencer version 4.5 (Gene Codes Corp, Ann Arbor, MI). Sequences were deposited in GenBank (http://www.ncbi.nlm.nih.gov/Genbank/index.html) under accession numbers HQ652332HQ652418.

Construction of the phylogenetic tree

Sequences of the partial mcrA genes were initially aligned using muscle (Edgar, 2004). Aligned sequences were imported into the arb program (Ludwig et al., 2004) and compared using a similarity matrix and then assigned to consensus groups. Nearest relatives were obtained from NCBI following blast comparison of consensus sequences. Also included within the alignment were mcrA genes from the whole genomic sequences of various methanogens. All sequences were re-aligned using muscle. The phylogenetic tree was generated using phylo_win program (Galtier et al., 1996) using the Nearest Neighbour Algorithm and a Jukes-Cantor correction (Jukes & Cantor, 1969) with pairwise gap removal. To statistically evaluate the tree, bootstrap values were calculated using data re-sampled 1000 times (Fellenstein, 1986).

Results

  1. Top of page
  2. Abstract
  3. Introduction
  4. Materials and methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References
  9. Supporting Information

LH-mcrA was used to assess the diversity and the structure of the methanogenic communities from a steady-state PFBR and two different manures, dairy and swine. Examples of LH-mcrA profiles from swine or dairy manures and from PF1 and PF8 of the PFBR are shown in Fig. 1. The LH-mcrA profiles from these environments were different between each other, suggesting different methanogenic archaeal communities. The LH-mcrA profile from swine manure was dominated by the 485-bp amplicon, whereas the profile from dairy cow manure mainly comprised the 464-, 481- and 485-bp amplicons. The LH-mcrA profile from PF1 of the PFBR comprised major amplicons at 485, 483 and 467 bp (40%, 26% and 20%, respectively; Table 1). The LH-mcrA profile from PF8 of the PFBR was mainly composed of the 483-bp amplicon (Table 1).

image

Figure 1. LH-mcrA profiles from environmental and engineered samples. (a) Swine manure, (b) dairy manure, (c) plug flow bioreactor first compartment and (d) plug flow bioreactor last compartment. (e) Molecular weight standard (450, 490 and 500 bp shown).

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Table 1. LH-mcrA relative abundances compared with amplicon length and distribution of phylogenetic groups among mcrA gene library clones from bioreactor samples
Related toLH-mcrA (%)Amplicon length in libraries (bp)Library clones (%)a
PF1 (n = 3)PF8 (n = 3)Clone nameSeqbActualcSDcPF1 (n = 47)PF8 (n = 41)
  1. a

    In the first (PF1) and the last (PF8) compartment of the PFBR. Total number of clones in parenthesis.

  2. b

    Theoretical amplicon length from sequence alignment with the newly designed mcrA primers.

  3. c

    Amplicon LH-PCR of the mcrA gene (LH-mcrA) mean value from PCR triplicates with SD, for a given clone, using the newly designed mcrA primers.

  4. d

    Including Methanoculleus-485 bp-, Methanogenium- and Methanospirillaceae-related clones.

Methanoculleus-483 bp26707A6488483.10.223 (11)5 (2)
10D12488483.30.20 (0)3 (1)
7B2488483.00.12 (1)15 (6)
7C7488483.00.16 (3)44 (18)
7B7488482.80.12 (1)0 (0)
Methanoculleus-485 bp40d15d7A7488484.70.19 (4)5 (2)
7C12488485.00.12 (1)0 (0)
Methanogenium  7A3488484.90.16 (3)0 (0)
7A1488484.90.215 (7)8 (3)
Methanospirillaceae  7C2488485.30.12 (1)0 (0)
MethanocorpusculumNDND10G2488486.60.10 (0)3 (1)
Methanosarcinaceae337B11485480.80.24 (2)0 (0)
7D2485481.60.12 (1)3 (1)
Unidentified201310E9470466.20.10 (0)3 (1)
7B4470467.50.14 (2)0 (0)
7A2470466.30.26 (3)5 (2)
7B3470466.60.19 (4)10 (4)
Methanobacteriales1017A12467464.40.14 (2)0 (0)
7E1467463.90.22 (1)0 (0)

The LH-mcrA relative abundances obtained from the PFBR samples were compared with the distribution of clones from the corresponding libraries (Table 1). Clone libraries of partial mcrA genes from PF1 and PF8 of the PFBR after 6 months of operation were sequenced, and amplicons generated by these clones were screened using LH-mcrA. Methanoculleus spp. were more abundant in PF8 (72% of the clones) than in PF1 (44% of the clones). Two particular phylotypes (7B2 and 7C7; Fig. 2) related to Methanoculleus were located preferentially in PF8 (15% and 44% vs. 2% and 6% in PF1, respectively; Table 1). In addition, the phylotype 7A6, also related to Methanoculleus, was located preferentially in PF1 (23% vs. 5% in PF8; Table 1).

image

Figure 2. Phylogenetic tree of the mcrA gene. Phylogenetic tree derived from the alignment of mcrA DNA clones with previously reported mcrA and mrtA (when specified) sequences. Clones are indicated in bold and are designated as 7X# if they are from the clone library PF1 (from the first compartment of the bioreactor) or as 10X# if they are from the clone library PF8 (from the last compartment of a PFBR). Clones designated as 7X# which also occur in library PF8 are indicated by the symbol (●). Bar represents a 5% sequence divergence. The tree was generated by neighbour joining with Bootstrap values for 1000 permutations indicated at the branch points.

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Variability in amplicon lengths obtained from individual clones by LH-mcrA was determined by analysis of three separate PCRs. The SD in LH-mcrA amplicon length for one clone in each of the different operational taxonomic units or phylotypes (Fig. 2) ranged from 0.1 to 0.2 bp (Table 1). All partial mcrA gene sequences aligning into the order Methanomicrobiales had a 488-bp theoretical amplicon length (from sequencing) but had 483-, 485- or 487-bp phylotypes when experimentally screened by LH-mcrA (Table 1). The majority of the clones related to Methanoculleus had an amplicon length of 483 bp, except phylotypes 7A7 and 7C12 (both at 485-bp). The 7A7 phylotype represented 9% and 5% of the clones in the libraries from PF1 and PF8, respectively. Only one clone was retrieved in the libraries that corresponded to the 7C12 phylotype. The clones related to Methanogenium and Methanospirillaceae also had an amplicon length of 485 bp. One clone was related to Methanocorpusculum and had a length of 486.6 bp. Partial mcrA gene sequences aligning within the Methanosarcinaceae family and the Methanobrevibacter spp. had an experimental amplicon length of 481 and 464 bp, respectively. A cluster of unidentified clones (Fig. 2) had amplicon lengths ranging from 466 to 467 bp and were evenly distributed in both PF1 and PF8. Overall, relative abundances using LH-mcrA were in agreement with clone library analyses (Table 1): (1) the 483-bp amplicon accounted for 26% and 70% compared with 33% and 67% of the corresponding clones; (2) the 485-bp amplicon accounted for 40% and 15% compared with 34% and 13% of the clones; and (3) the 467-bp amplicon was present at 20% and 13% compared with 19% and 18%; in PF1 and PF8, respectively.

One concern with this method is that the variation in amplicon length that distinguishes the Methanomicrobiales and Methanosarcinaceae is only 2 bp (481-, 483- and 485-bp amplicons). Capillary electrophoresis clearly resolved these methanogen groups in mixtures of clones (Supporting Information, Fig. S1 and technical details in Appendix S1). The SD of the amplicon lengths determined on five replicated PCRs ranged between 0.1–0.4 bp (Table S1 in Appendix S2).

To test more directly the quantitative aspect of the novel LH-mcrA fingerprint method, PCR products from five different clones having amplicon lengths of 464, 467, 481, 483 or 485 bp were purified and mixed in equal proportion to be used as DNA template in LH-mcrA PCRs. A mean relative abundance and SD of 20.0 ± 3.7% with minimum (for the 483-bp amplicon) and maximum (for the 464-bp amplicon) relative abundances of 13% and 25%, respectively (Table S2 in Appendix S2), were obtained from five LH-mcrA replicated analyses (Table 2, Mixed clones). The possibility of PCR bias that could have effects on peak heights in a LH-mcrA profile was evaluated by comparing the variation in peaks height from the above LH-mcrA profile with the variation from a LH-mcrA profile obtained by mixing LH-mcrA amplicons from individual clones in equimolar proportions before capillary electrophoresis. Under these conditions, the SD was 1.1% (Table 2, mixed amplicons), and relative abundances varied from 18.7% to 22.0% (Table S3 in Appendix S2). The influence of the vicinity of the peaks on LH-mcrA data was evaluated by comparing the LH-mcrA profile from the mixed amplicons with a profile generated by overlaying individual electrophoretic migrations of each clone (Fig. S1b). This resulted in an artificial profile with peak heights varying from 17.7% to 21.7% with a mean value of 20.0 ± 1.4% (Table 2, individual clones).

Table 2. Quantitative analysis of LH-mcrA profiling by capillary electrophoresis
LH-mcrA template or ampliconRelative abundance of LH-mcrA amplicons (%)aMean
464-bp467-bp481-bp483-bp485-bp
  1. a

    Mean values and standard deviation.

  2. b

    Templates are a pool of purified PCR products (LH-mcrA amplicons) from the mixture of five clones (mixed clones, = 5) or from each individual clones (artificial profile, = 2).

  3. c

    LH-mcrA amplicons from the five individual clones mixed prior to capillary electrophoresis (= 3).

Mixed clonesb24.5 ± 0.320.1 ± 0.422.0 ± 0.613.5 ± 0.419.9 ± 0.420.0 ± 3.7
Mixed ampliconsc20.8 ± 0.319.2 ± 0.319.0 ± 0.419.4 ± 0.321.7 ± 0.320.0 ± 1.1
Individual clonesb19.0 ± 1.921.0 ± 0.520.7 ± 1.420.2 ± 2.219.2 ± 0.520.0 ± 1.4

Discussion

  1. Top of page
  2. Abstract
  3. Introduction
  4. Materials and methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References
  9. Supporting Information

This is the first time that the structure and diversity of archaeal communities are estimated by LH-PCR using a functional gene. One can therefore estimate simultaneously the diversity of a functional group and the relative expression level of this gene (mRNA level) from the different members of this group. Even though T-RFLP based on the mcrA gene has already been reported as a valuable tool for this purpose (Lueders et al., 2001), LH-PCR is less expensive (Talbot et al., 2008), more reproducible (Mills et al., 2003) and more rapid than T-RFLP. In contrast to LH-mcrA, T-RFLP requires that PCR products are first purified and de-salted using a commercial kit followed by a restriction digestion step for several hours. The cost for T-RFLP is therefore increased by a factor of approximately 250% (ca. 3.50$ instead of 1$ per DNA sample) by comparison with LH-mcrA. Incomplete enzymatic restriction digestion may affect reproducibility in T-RFLP data (Mills et al., 2003). All those advantages LH-mcrA offers are promising to assess changes in methanogenic archaeal communities in biosystems at low cost and quickly.

As suggested by LH-mcrA profiling and clone library analysis from the PFBR, the methanogenic archaeal communities in swine manure would tentatively be mainly composed of members from the Order Methanomicrobiales, which is in agreement with T-RFLP results based on the 16S rRNA gene on other swine manure samples (Talbot et al., 2009). LH-mcrA profiling suggested that the methanogenic community in the dairy manure sample would mainly be composed of members in the Methanomicrobiales order including the Methanobrevibacter spp., and members of the Methanosarcinaceae. The presence of Methanobrevibacter spp. in dairy manure methanogenic communities is in agreement with their dominance in bovine rumen (Whitford et al., 2001). However, one should remind that the LH-mcrA method has to be coupled to clone library analysis from the same environmental samples for an accurate phylogenetic identification of the peaks.

The phylogenetic resolution of the LH-mcrA method was studied by combining clone library analysis to LH-mcrA data. The Methanoculleus-related phylotypes were not only found in the 483-bp amplicon: some of them were comprised in the 485-bp amplicon. This limitation in discriminating the 7A7 and 7C12 phylotypes from other phylotypes related to Methanogenium and Methanospirillaceae would possibly be attributable to slight mobility differences caused by single-stranded secondary structure differences during capillary electrophoresis (Boyd et al., 2006). Secondary structure depends on the nucleotide sequence and would also explain why all the clones having 488-bp sequence length do not have the same apparent LH-mcrA amplicon length.

Fingerprint data need to be interpreted cautiously because of possible PCR bias. Lueders & Friedrich (2003) concluded in a study comparing T-RFLP analysis of 16S rRNA and mcrA genes that PCR bias could be evaluated by the quantification of a pool of PCR products. Peak heights variation in LH-mcrA profiles obtained from a pool of PCR products from five clones in equimolar proportions was compared with the variation in LH-mcrA data obtained from LH-mcrA amplicons from these five clones mixed prior to electrophoresis and suggested a slight PCR bias. The relative abundances had a small global SD (3.7%) from the pool of PCR products, which is acceptable for a fingerprinting method (Lueders & Friedrich, 2003). In addition, the global SD obtained from mixed individual LH-mcrA amplicons from the five clones was as low as the global SD obtained from the artificial LH-mcrA profile obtained from individual runs of each of these clones (1.1% compared with 1.4%, respectively). This finding suggests that the vicinity of the peaks had no actual influence on relative abundance.

Cloning and sequencing combined with analysis using individual clones or a pool of PCR products from these clones confirmed that profiles generated by LH-mcrA could accurately assess the diversity and the relative abundance of methanogens in bioreactor samples. Phylogenetic analysis showed that our clones were all related to methanogens (not methane-oxidizing Archaea) and mcrA genes (not mrtA genes). However, the primer set designed and used in this study could have amplified the mcrA gene from methane-oxidizing Archaea or the mrtA gene. LH-mcrA has thus the potential to unravel the diversity of more complex archaeal communities than the ones examined here.

Methanoculleus spp. are hydrogenotrophic methanogens, and LH-mcrA results combined with cloning–sequencing results confirmed our hypothesis that hydrogenotrophic methanogens would have a major role in this PFBR treating swine manure (Talbot et al., 2010). Hence, the LH-mcrA profiles are not only consistent with clone libraries as discussed earlier, but they would also be reflective of the functional aspects of these communities.

We are currently assessing the relative expression level of mcrA genes in our samples by reverse transcription LH-mcrA (RT-LH-mcrA). This merits to be further investigated because the relationship between the mcrA gene transcription and the methanogenesis in complex systems is not well understood yet (Freitag & Prosser, 2009). RT-LH-mcrA may better reflect the relative metabolic activity of specific methanogenic groups in ecosystems than would be the mere presence of 16S rRNA genes or molecules.

In conclusion, the novel LH-mcrA fingerprint method may represent a valuable tool to estimate both the relative abundance and the diversity of archaeal methanogens in microbial systems. This high-throughput method could be useful for continued bioreactor monitoring with a view of predicting eventual failures.

Acknowledgements

  1. Top of page
  2. Abstract
  3. Introduction
  4. Materials and methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References
  9. Supporting Information

We thank Frédéric Tremblay, Nicolas Chaput and Bruno Morissette for technical help and Stephen Brooks for sequencing. This work was funded by Agriculture and Agri-Food Canada Sustainable Agriculture Environmental Systems (SAGES) research program.

References

  1. Top of page
  2. Abstract
  3. Introduction
  4. Materials and methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References
  9. Supporting Information
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Supporting Information

  1. Top of page
  2. Abstract
  3. Introduction
  4. Materials and methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References
  9. Supporting Information
FilenameFormatSizeDescription
fml2418-sup-0001-FigS1.docWord document64KFig. S1. LH-mcrA profiles from (a) a pool of five purified PCR products from five clones amplified together in one PCR reaction and (b) overlays of individual capillary electrophoresis runs from these five clones amplified separately. (c) Molecular weight standard (450, 490 and 500 bp shown).
fml2418-sup-0002-tableS1.docxWord document15KTable S1. Amplicon length analysis for a pool of five PCR products from five clones.
fml2418-sup-0003-tableS2.docxWord document18KTable S2. Relative abundance for a pool of five PCR products from five clones.
fml2418-sup-0004-tableS3.docxWord document16KTable S3. Relative abundance of LH-mcrA amplicons (from each individual clones) mixed together before capillary electrophoresis.

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