Automated DNA extraction platforms offer solutions to challenges of assessing microbial biofouling in oil production facilities
© Oldham et al.; licensee Springer. 2012
Received: 9 November 2012
Accepted: 16 November 2012
Published: 20 November 2012
The analysis of microbial assemblages in industrial, marine, and medical systems can inform decisions regarding quality control or mitigation. Modern molecular approaches to detect, characterize, and quantify microorganisms provide rapid and thorough measures unbiased by the need for cultivation. The requirement of timely extraction of high quality nucleic acids for molecular analysis is faced with specific challenges when used to study the influence of microorganisms on oil production. Production facilities are often ill equipped for nucleic acid extraction techniques, making the preservation and transportation of samples off-site a priority. As a potential solution, the possibility of extracting nucleic acids on-site using automated platforms was tested. The performance of two such platforms, the Fujifilm QuickGene-Mini80™ and Promega Maxwell®16 was compared to a widely used manual extraction kit, MOBIO PowerBiofilm™ DNA Isolation Kit, in terms of ease of operation, DNA quality, and microbial community composition. Three pipeline biofilm samples were chosen for these comparisons; two contained crude oil and corrosion products and the third transported seawater. Overall, the two more automated extraction platforms produced higher DNA yields than the manual approach. DNA quality was evaluated for amplification by quantitative PCR (qPCR) and end-point PCR to generate 454 pyrosequencing libraries for 16S rRNA microbial community analysis. Microbial community structure, as assessed by DGGE analysis and pyrosequencing, was comparable among the three extraction methods. Therefore, the use of automated extraction platforms should enhance the feasibility of rapidly evaluating microbial biofouling at remote locations or those with limited resources.
Keywords16S rRNA gene Automated nucleic acid extraction platforms Microbial biofouling Bacterial community Oilfield microbiology
Microbial biofouling is a significant problem facing many different systems including industrial (e.g. fuel production, food production, drinking-water, etc.), marine (e.g. ship ballast tanks) and medical (e.g. catheters) (Bixler and Bhushan2012). Biofilm formation, or the accumulation of water-borne microorganisms and their associated extrapolymeric substances (EPS) on wetted surfaces, is a major contributor to biofouling and becomes an economic liability when it exceeds some threshold of interference, resulting in material damage, production loss, or elevated health risks (Murthy and Venkatesan2009). Therefore, rapid sample processing and analysis is necessary for prompt microbial biofouling assessment. Due to limited space, resources, or expertise, samples from the facilities at risk are often shipped to research or commercial laboratories for nucleic acid extraction and analysis, where the efficacy of antifouling approaches, such as biocide treatment or physical biofilm removal (Quarini and Shire2007), can be rapidly deduced using molecular-based approaches. These approaches include amplification of both the 16S rRNA gene and functional genes to identify specific microbes and qPCR to quantify target genes (Smith and Osborn2009). The caveats of shipping samples for extraction in lieu of extracting on-site include: 1) shipping materials that could be considered "hazardous," and 2) the microbial community structure of the sample could shift during the time in transit from facility to lab, leading to erroneous results. Therefore, the ability to extract nucleic acids on-site and within hours of sampling could bypass these two caveats and hasten microbial biofouling assessment and treatment.
Comparison of DNA extraction platforms
Ease of operation
Nucleic acid mobilization
3 x Washes
120 min (n = 10)
60 min (n = 8)
45 min (n = 16)
Physical lysis equipmentb
Cost (per sample)
Our lab has extensive experience with traditional phenol-chloroform DNA extractions and with using a broad array of commercially available extraction kits, both of which require ancillary laboratory equipment. The goal of this study was to test the feasibility of using more automated extraction approaches on biofilm material scraped from oilfield pipelines, as an example of the types of complex samples encountered in industrial situations. We hypothesized that the two automated platforms chosen would perform equivalently to a widely used manual extraction kit when compared by a set of standard PCR-based analyses. The rationale for this study was to determine if more automated extraction platforms would enable personnel, untrained in molecular biology or with limited laboratory resources, to extract DNA on-site and within hours to preserve sample integrity. The two automated extraction platforms tested were the semi-automated QuickGene-Mini80™ (Autogen/FujiFilm, Holliston, MA) and the automated Maxwell®16 (Promega, Madison, WI) platforms. Both systems were designed to extract nucleic acids from various tissues and cell types in clinical labs (Affolabi et al.2012) and both systems have proven successful for a wider variety of additional sample types including spores (Shipley et al.2012), plant leaves, seeds, and fungi (Affolabi et al.2012; Foley et al.2011; Khokhar et al.2011; Schagat et al.2007). The manual kit, PowerBiofilm DNA Isolation Kit (MOBIO Laboratories, Carlsbad, CA), was designed to extract DNA from biofilm material and is representative of the kits widely used by environmental microbiologists (Ferrando and Tarlera2009; McBeth et al.2010). For the three test samples, we compared extraction platform ease of use and DNA yields. A series of PCR-based analyses was then used to assess DNA extract quality and effect on microbial community profiles.
Materials and methods
Pipeline biofilm samples
Three samples scraped from the inner surface of oilfield pipelines (i.e. pigged pipeline material) were collected and stored at −80°C. Two of the samples, designated "A" and "B", originated from pipelines carrying produced water being returned to the formation to maintain pressure. A third sample, "C", originated from a pipeline as part of a seawater injection system for secondary oil recovery. Samples A and B contained crude oil, corrosion products such as iron sulfides and biofilm material (e.g. EPS). Sample C did not contain crude oil but did contain lesser quantities of corrosion products and biofilm material. For samples A, B, and C, DNA was extracted from ten aliquots (subsamples) for each extraction platform. For samples A and B (40 ml), each was thawed at 4°C, mixed, and ten replicate subsamples (0.5 ml) were dispensed into 2 ml conical screw-top tubes. Sample C (40 ml) was thawed, mixed, and ten replicate subsamples (1 ml) were dispensed into 2 ml conical tubes and concentrated by centrifugation for 5 min at 14000 × g, removing 0.5 ml of the supernatant and re-suspending the remaining volume. This concentration of biomass was deemed necessary for sample C, as initial studies revealed it contained 1/10th of the biomass of samples A or B (personal communication, Kathleen Duncan).
MOBIO PowerBiofilm extraction platform
The PowerBiofilm DNA Isolation Kit (MOBIO Laboratories) was used to manually extract DNA from ten replicate subsamples of samples A, B, and C according to the manufacturer's instructions. Specifically, the contents of a PowerBiofilm bead tube, and 350 μl of buffer BF1 and 100 μl of buffer BF2 were added to each sample tube. Samples were vortexed and incubated at 65°C for 5 min. Physical lysis of cell material was accomplished using the Mini-BeadBeater-16 (BioSpec Products, Bartlesville, OK) at 3450 oscillations/min for 2 min. Samples were spun at 13000 × g for 1 min. Supernatants were transferred to fresh tubes and 200 μl of buffer BF3 were added; samples were incubated at 4°C for 5 min and subsequently spun for 1 min. Supernatants were transferred to fresh tubes and 900 μl of buffer BF4 were added and samples mixed. Samples were loaded onto a PowerBiofilm spin filter column and spun for 1 min repeatedly until all sample was collected onto the filter. Filters were washed with 650 μl of buffer BF5 followed by buffer BF6 and ended with a final spin for 2 min. DNA was eluted in 100 μl of buffer BF7 with a final spin for 1 min.
Fujifilm QuickGene-Mini80 extraction platform
DNA was extracted from ten replicate subsamples of A, B, and C using the QuickGene DNA Tissue Kit S with the semi-automated QuickGene-Mini80 instrument (Autogen/FujiFilm, Holliston, MA) following manufacturer's instructions. Cell lysis was facilitated by adding 180 μl of Tissue lysis buffer (Autogen/FujiFilm) and 20 μl Proteinase K to each sample tube and mixing with a Thermolyne LabQuake Rotisserie Tube Shaker (ThermoScientific/Barnstead, Waltham, MA) for 30 min at 55°C. Samples were spun at 10000 × g for 3 min. The supernatants were transferred to a new tube and 20 μl RNase A were added and incubated for 2 min. Next, 180 μl Lysis buffer and 240 μl ethanol (>99%) were added and the sample was vortexed for 15 s. Samples were transferred to QuickGene cartridges and placed within the QuickGene Mini80 apparatus, and DNA binding, washing, and elution were accomplished through pressurization. DNA was eluted with 200 μl Elution buffer.
Promega Maxwell 16 extraction platform
DNA was extracted from ten replicate subsamples of A, B, and C using the automated Maxwell 16 Cell Total RNA Purification Kit with the Maxwell 16 Instrument (Promega) set to the LEV (low elution volume) configuration. Specifically, samples were loaded into the pre-dispensed reagent cartridges along with 400 μl RNA lysis buffer and 400 μl RNA dilution buffer. Elution tubes containing 100 μl nuclease-free water, plungers, and cartridges containing the sample and buffers were placed within the instrument and all subsequent steps were automated following the pre-programmed DNA extraction protocol. The DNA-removal steps of the Total RNA Purification Kit protocol were omitted to preserve the DNA (Promega Field Application Specialist, personal communication).
Evaluation of extracted DNA yield
DNA extracts from the subsamples were analyzed by gel electrophoresis and quantified using fluorometry to compare the reproducibility of extraction among replicate samples. To visualize the DNA fragment, 10 μl of each extract was analyzed alongside 2 μl of Lambda DNA/EcoRI+HindIII marker (ThermoFisherScientific/Fermentas, GlenBurnie, MD) on a 1% agarose gel (wt/vol) stained with SYBR®Safe (Invitrogen, Carlsbad, CA). Gels were visualized and the image captured using the Gel Logic 112 Imaging System and Molecular Imaging Software v5 (Carestream, WoodBridge, CT). DNA extracts were quantified using the Qubit 2.0 fluorometer with the dsDNA or RNA reagents according to the manufacturer’s protocol (Invitrogen/Life Technologies, Carlsbad, CA). GraphPad Prism5 (GraphPad Software, San Diego, CA) was used to generate box-and-whisker plots to visualize the degree of variation in DNA yields among replicate extractions. Upper and lower whiskers illustrate the maximum and minimum DNA yields, respectively, and the median DNA yield separates the box into upper (75%) and lower (25%) quartiles.
For each of the three platforms, the ten subsample DNA extracts were pooled to generate DNA stocks for subsequent analyses to assess DNA extract quality and its effect on the microbial community structure, while minimizing the effect of small sample volumes. For each of the three samples A, B, and C, the total amount of DNA extracted from equivalent sample volumes for each platform was determined by multiplying the concentration of each of the ten subsample extractions by its elution volume and summing the products.
Evaluation of extracted DNA quality using qPCR analysis
Evaluation of the influence of DNA extraction platform on microbial community composition using denaturing gradient gel electrophoresis (DGGE)
A DGGE analysis of amplified bacterial 16S rRNA genes was used to evaluate potential biases in cell lysis between extraction platforms. Briefly, 2 μl of DNA were amplified by end-point PCR in 25 μl reactions. Each reaction contained: 0.625 U DreamTaq™ polymerase (Fermentas, Glen Burnie, MD), 0.2 mM dNTP mixture, 0.5 M betaine, 1 × DreamTaq Buffer (Fermentas), and 100 nM each of forward primer GM5F (5′-CCTACGGGAGGCAGCAG) containing the GC clamp on the 5'-end and reverse primer D907R (5′-CCCCGTCAATTCCTTTGAGTTT) (Santegoeds et al.1999). Thermal cycling was carried out with a TC-512 thermal cycler (Techne, Burlington, NJ) using a touchdown PCR program from 65°C to 55°C. Conditions were 94°C for 4 min, followed by 2 cycles each of 94°C for 1 min, N°C for 1 min, and 72°C for 1 min, where N°C dropped 1°C from 65°C to 55°C, followed by 15 cycles at the 55°C annealing temperature and a final extension at 72°C for 10 min. For bacterial community analysis, 15 μl of each reaction was resolved on a 6% polyacrylamide, urea and formamide 40-60% denaturing gradient gel (100% denaturant = 7 M Urea and 40% formamide) (Muyzer et al.1993) and run at 65 V for 16 h at 60°C. The gel was stained for 15 min in SYBR Safe (at 25 μl per 250 ml) and visualized as described above.
Identification of microbial community composition among DNA extracts using high throughput sequencing of 16S rRNA gene libraries
To identify major bacterial taxa in samples A, B, and C DNA extracts, bacterial 16S rRNA gene libraries were generated from each extraction method modeled after the approach used by Wawrik et al. (2011). For each sample, triplicate 50 μl reactions contained 5 μl to 10 μl DNA, 1.25 U DreamTaq polymerase, 0.2 mM dNTP mixture, 0.5 M betaine, 1xDreamTaq Buffer (Fermentas), 250 nM 27f and 125nM 338r primers. Thermal cycling was carried out on a TC-512 thermal cycler (Techne) with the following conditions: 96°C for 3 min; 30 cycles of 96°C for 30 s, 55°C for 45 s, 72°C for 45 s; and a final extension at 72°C for 10 min. Triplicate reactions were pooled and purified using the Wizard PCR Preps DNA Purification System (Promega). From each of the purified PCRs, 5 μl was added to a second PCR containing barcoded PCR primers TiA-8nt-CA-27f (5′-CCATCTCATCCCTGCGTGTCTCCGACTCAGxxxxxxxxCAAGAGTTTGATCCTGG CTCAG) and TiB-CA-338r (5′-CCTATCCCCTGTGTGCCTTGGCAGTCTCAGCA TGCTGCCTCCCGTAGGAGT) for multiplexed pyrosequencing as described by Hamady et al. (2008). Each sample received a different tagged forward primer, containing a specific 8 nt ‘barcode’ sequence (designated by x), and samples were ‘tagged’ by re-amplification for six cycles. Barcodes are listed in Additional file1: Table S1. The efficacy of the tagging reaction was confirmed by gel electrophoresis. Tagged PCR products were pooled in equimolar amounts and sequenced on a GS-FLX sequencer using the Titanium chemistry at (University of Oklahoma's Advanced Center for Genome Technology2012).
The bacterial 16S rRNA gene libraries were analyzed using the bioinformatics software package, mothur ver1.24 (Schloss et al.2009). An implementation of the Amplicon Noise algorithm was used to reduce the sequencing error incurred with pyrosequencing (Quince et al.2011). Sequences were binned by barcode and screened to remove those containing errors in the forward primer or barcode. Unique sequences were trimmed to overlap a minimum of 200 base pairs and aligned against the SILVA reference alignment database (Pruesse et al.2007) using the NAST-aligner (DeSantis et al.2006). Sequences were pre-clustered using a single linkage algorithm (Huse et al.2010) to reduce the number of spurious operational taxonomic units (OTUs) that would result from pyrosequencing errors, and subsequently screened for chimeras using UChime (Edgar et al.2011). A distance matrix was generated and used to cluster sequences into OTUs at a 97% similarity level using the furthest neighbor algorithm. A representative sequence from each OTU was assigned a taxonomic classification based on the Ribosomal Database Project's naïve Bayesian classifier (Wang et al.2007) at an 80% confidence threshold; and all richness and diversity measurements were calculated using the mothur software package based on a random subsampling subset of 1958 sequences to equal the number of reads in the smallest library. Using the generated distance matrix, an analysis of molecular variance (AMOVA) was used to determine if the observed differences in microbial diversity between sample groups or extraction methods was significantly different (Schloss2008; Schloss and Handelsman2008). Sequences were deposited in the short read archive of GenBank [GenBank: SRA052225].
DNA extraction platform ease of use and cost considerations
The ease of use and cost parameters for the three extraction platforms are compared in Table 1. For PowerBiofilm, all steps from sample preparation to DNA elution were manual and additional equipment for sample processing included a microcentrifuge, bead-beater, incubator, and refrigerator. With multiple centrifugations, sample transfers, and incubation steps, the total processing time was approximately 120 min for ten samples. For the QuickGene Mini-80, initial sample processing steps were similar to that of PowerBiofilm with centrifugations and incubations for sample preparation and cell lysis, but DNA binding, washes, and elution were streamlined to process eight samples in parallel using pressure filtration technology. The total processing time was approximately 60 min, which included a 30 min incubation step for cell lysis. The Maxwell 16 platform required the least manual manipulation, with the transfer of sample plus lysis and dilution buffers to pre-filled reagent cartridges. The only other manual steps required for extraction set up were the addition of elution buffer, collection tubes and plungers into the cartridge-holder. All subsequent steps from cell lysis to nucleic acid elution were fully automated using pre-programmed settings and up to 16 samples could be processed in parallel. Extraction times for the two more automated platforms were less than half that as the manual method. Additional equipment requirements for sample processing were similar for PowerBiofilm and QuickGene; both required a microcentrifuge and incubator for processing steps as well as equipment for cell lysis. No additional equipment was necessary for the Maxwell 16 platform aside from the instrument itself. With regard to price per sample, consumable supplies for PowerBiofilm and Maxwell were similarly priced, whereas QuickGene was approximately one-third less (Table 1).
Comparison of DNA yield between extraction platforms from equivalent starting sample volumes
Assessment of extracted DNA quality (i.e. PCR inhibition) by qPCR amplification in undiluted and diluted DNA extracts
Evaluation of PCR inhibition via bacterial 16S rRNA gene amplification in undiluted (1x) versus diluted DNA extracts a
Effect of DNA extraction platform on bacterial community composition by DGGE analysis
Identification of bacterial communities in DNA extracts using 454 pyrosequencing
In lieu of lengthy and potentially biased culturing methods, PCR-based analyses are an adequate and much less time-consuming alterative to monitoring microbial biofouling (Filion2012). However, the interval between sample collection and analysis can influence the microbial community structure (Rochelle et al.1994; van der Kraan et al.2010) leading to erroneous results and complicating the ability to correctly assess fouling severity. Commercially available kits yield high-quality nucleic acids, but time-consuming sample processing and the requirements for additional equipment largely limits their use to molecular biology labs. Therefore, more automated nucleic acid extraction platforms were evaluated for potential use in performing DNA extractions in remote areas or with limited laboratory facilities. Automated platforms provide several practical advantages: 1) the ability to process samples in remote locations, 2) on-site extractions bypass the shipment of potentially hazardous samples, 3) reducing the training needed for personnel conducting the nucleic acid extraction, and 4) reducing time to implement corrective measures. Findings presented here demonstrated that the more automated methods were successful in extracting DNA from both high- and lower-biomass biofilm samples scraped from the inner surface of oil pipelines and that all three extraction platforms produced high-quality DNA suitable for PCR-based analyses.
The PowerBiofilm extraction platform included repeated vortexing, sample transfers, centrifugations, incubations, and additional equipment needed for processing steps. Personnel with some molecular biology experience are best suited for this level of sample manipulation. In addition to the need for technical expertise, variability in extraction reproducibility among subsamples (Figure 1a) warranted the consideration of alternate extraction platforms. The QuickGene platform also required manual steps for sample preparation and cell lysis, but the QuickGene-Mini80 instrument streamlined the binding, washing and elution using pressure filtration and could process up to eight samples simultaneously. Both QuickGene and PowerBiofilm platforms use column chromatography for DNA capture. QuickGene provided greater reproducibility and higher DNA yields for the high biomass samples, but still required ancillary equipment for sample preparation. The Maxwell method provided the best overall performance in terms of the ease of use and DNA yields for both high- and lower-biomass samples. The Maxwell 16 instrument, with the footprint of a microwave oven, is readily transportable for use in the field and can processes 16 samples simultaneously. Sample processing was completely automated, requiring no ancillary equipment and only minimal technical experience was required. These properties make the Maxwell system a better choice for DNA extractions at remote locations for the sample types tested.
Estimates of 16S rRNA gene copies per ml original sample corroborated the quantitative differences in DNA yields. Many variables between the three platforms could account for the differences in extraction efficiency. One variable that is correlated to efficiency is the format of the matrix used to bind DNA (Kephart et al.2006). QuickGene utilizes a specialized high-capacity DNA-binding membrane ~1/12.5 the thickness of traditional glass membranes and the Maxwell uses silica-coated paramagnetic beads to bind nucleic acids. These beads are transferred to adjacent wells for washing and elution of DNA. The magnetic beads may have a greater binding-capacity or opportunity to bind DNA than the filter matrices used with the PowerBiofilm (or QuickGene) platform. The filter formats may also retain a greater amount of contaminating compounds, yet all downstream analyses indicated that the DNA from each method was of high quality. Differences in cell lysis between each extraction platform were identified as a potential concern, as differences in the community analysis may result if complete lysis was not achieved (Frostegård et al.1999; Krsek and Wellington1999). The PowerBiofilm and Maxwell platforms included physical disruption via bead-beating or plunging activity by a magnetic rod respectively, whereas lysis by the QuickGene platform was accomplished through sample rotation at elevated temperature. Both DGGE and pyrosequencing of PCR-amplified 16S rRNA genes, however, showed that the structures of the microbial communities surveyed were minimally affected by the method of DNA extraction (Figures 3 through5). Importantly, the three extraction platforms showed similar proportions in the dominant gram-positive Firmicutes in sample A (56%-P, 53%-Q 48%-M), demonstrating that these three extraction platforms were capable of lysing cells with tough cell walls, which may be present in other complex samples.
The conclusion drawn from pyrosequencing data was made with caution as variation between technical replicates, replicate samples, and identical samples from one sequencing run to another has been documented (Zhou et al.2011 and Schloss et al.2011). With the number of singletons (single sequence-containing OTUs) ranging from 12 to 33 for each sample A replicate library, the variation observed for the OTU analysis was expected, as was that observed between the separate sequencing runs for the single (Figure 4) versus replicate (Figure 5) sample A analyses (i.e. gram-positive Firmicutes remained dominant at 50-60% and 70-75%, respectively). Therefore, while biases between extraction methods are noted in the literature (Stach et al.2001), the variation observed in 454 pyrosequencing studies presented here may be primarily the result of variation arising during post-nucleic acid extraction processes (Schloss et al.2011; Zhou et al.2011).
The Promega Maxwell 16 platform's portability and ease of use make it an attractive alternative to manual extractions if space is a limitation. The Maxwell 16 has several advantages over the Powerbiofilm and QuickGene Mini-80 platforms. First, the Maxwell 16 requires no additional equipment for sample processing, resulting in minimal sample handling. Second, the small size allows transport for use in mobile labs, where samples taken from remote sites could be processed within hours of procurement. Third, up to 16 samples are ready for PCR-based analyses within an hour of processing ensuring that shifts in bacterial communities are minimal. We conclude that the QuickGene and Maxwell platforms are examples of suitable alternatives for molecular analysis of microbial biofouling, and that automated DNA extraction platforms from a variety of manufacturers may facilitate microbial contaminant assessment in many industrial settings.
We gratefully acknowledge support from the University of Oklahoma Biocorrosion Research Center Consortium sponsored by ConocoPhillips, grant SRA FY10-ORA3-24. The authors would also like to thank Dr. Fares Najar for technical assistance with submitting libraries to GenBank. The conclusions expressed in this paper are those of the authors and not necessarily shared by the Biocorrosion Center or ConocoPhillips. We thank the Promega Corporation for loan of the Maxwell-16 instrument and FujiFilm for the QuickGene Mini80 instrument.
- University of Oklahoma's Advanced Center for Genome Technology 2012.Google Scholar
- Affolabi D, Sanoussi N, Vandelannoote K, Odoun M, Faïhun F, Sopoh G, Anagonou S, Portaels F, Eddyani M: Effects of decontamination, DNA extraction, and amplification procedures on the molecular diagnosis of Mycobacterium ulcerans disease (Buruli ulcer). J Clin Microbiol 2012,50(4):1195–1198. 10.1128/JCM.05592-11PubMed CentralView ArticlePubMedGoogle Scholar
- Bixler GD, Bhushan B: Biofouling: lessons from nature. Philos Transact A Math Phys Eng Sci 2012, 370: 2381–2417. 10.1098/rsta.2011.0502View ArticleGoogle Scholar
- DeSantis TZ Jr, Hugenholtz P, Keller K, Brodie EL, Larsen N, Piceno YM, Phan R, Andersen GL: NAST: a multiple sequence alignment server for comparative analysis of 16S rRNA genes. Nucleic Acids Res 2006. 10.1093/nar/gk1244Google Scholar
- Edgar RC, Haas BJ, Clemente JC, Quince C, Knight R: UCHIME improves sensitivity and speed of chimera detection. Bioinformatics 2011,27(16):2194–2200. 10.1093/bioinformatics/btr381PubMed CentralView ArticlePubMedGoogle Scholar
- Ferrando L, Tarlera S: Activity and diversity of methanotrophs in the soil–water interface and rhizospheric soil from a flooded temperate rice field. J Appl Microbiol 2009,106(1):306–316. 10.1111/j.1365-2672.2008.04004.xView ArticlePubMedGoogle Scholar
- Filion M: Quantitative real-time PCR in Applied Microbiology. Caister Academic Press Place, Norfolk; 2012.Google Scholar
- Foley C, O'Farrelly C, Meade KG: Technical note: Comparative analyses of the quality and yield of genomic DNA from invasive and noninvasive, automated and manual extraction methods. J Dairy Sci 2011,94(6):3159–3165. 10.3168/jds.2010-3987View ArticlePubMedGoogle Scholar
- Frostegård A, Courtois S, Ramisse V, Clerc S, Bernillon D, Le Gall F, Jeannin P, Nesme X, Simonet P: Quantification of bias related to the extraction of DNA directly from soils. Appl Environ Microbiol 1999,65(12):5409–5420.PubMed CentralPubMedGoogle Scholar
- Hamady M, Walker JJ, Harris JK, Gold NJ, Knight R: Error-correcting barcoded primers for pyrosequencing hundreds of samples in multiplex. Nat Methods 2008,5(3):235–237. 10.1038/nmeth.1184PubMed CentralView ArticlePubMedGoogle Scholar
- Huse SM, Welch DM, Morrison HG, Sogin ML: Ironing out the wrinkles in the rare biosphere through improved OTU clustering. Environ Microbiol 2010,12(7):1889–1898. 10.1111/j.1462-2920.2010.02193.xPubMed CentralView ArticlePubMedGoogle Scholar
- Kephart D, Krueger S, Grunst T, Shenoi H: Introducing the Maxwell 16 instrument: a simple, robust and flexible tool for DNA Purification. 2006. Promega Notes 92:20–23. Available viadocument. Accessed 07 November 2012 http://www.promega.com/resources/articles/pubhub/promega-notes-2006/introducing-the-maxwell-16-instrument-a-simple-robust-and-flexible-tool-for-dna-purificationGoogle Scholar
- Khokhar SK, Mitui M, Leos NK, Rogers BB, Park JY: Evaluation of Maxwell® 16 for automated DNA extraction from whole blood and formalin-fixed paraffin embedded (FFPE) tissue. Clin Chem Lab Med 2011,50(2):267–272.PubMedGoogle Scholar
- Krsek M, Wellington EM: Comparison of different methods for the isolation and purification of total community DNA from soil. J Microbiol Methods 1999,39(1):1–16. 10.1016/S0167-7012(99)00093-7View ArticlePubMedGoogle Scholar
- McBeth JM, Little BJ, Ray RI, Farrar KM, Emerson D: Neutrophilic iron-oxidizing “zetaproteobacteria” and mild steel corrosion in nearshore marine environments. Appl Environ Microbiol 2010,77(4):1405–1412.PubMed CentralView ArticlePubMedGoogle Scholar
- McKew BA, Smith CJ: Real-Time PCR approaches for analysis of hydrocarbon-degrading bacterial communities. In Handbook of hydrocarbon and lipid microbiology. Edited by: Timmis KN. Springer-Verlag, Heidelberg; 2010.Google Scholar
- Murthy S, Venkatesan R: Industrial biofilms and their control. In Marine and industrial biofouling. Edited by: Flemming HC, Murthy PS, Venkatesan R, Cooksey KC. Springer-Verlag, Heidelberg; 2009.Google Scholar
- Muyzer G, de Waal EC, Uitterlinden AG: Profiling of complex microbial populations by denaturing gradient gel electrophoresis analysis of polymerase chain reaction-amplified genes coding for 16S rRNA. Appl Environ Microbiol 1993,59(3):695–700.PubMed CentralPubMedGoogle Scholar
- Pruesse E, Quast C, Knittel K, Fuchs BM, Ludwig W, Peplies J, Glockner FO: SILVA: a comprehensive online resource for quality checked and aligned ribosomal RNA sequence data compatible with ARB. Nucleic Acids Res 2007,35(21):7188–7196. 10.1093/nar/gkm864PubMed CentralView ArticlePubMedGoogle Scholar
- Quarini J, Shire S: A review of fluid-driven pipeline pigs and their applications. Proc IMEJ Proc Mech Eng 2007, 221: 1–10. 10.1243/0954408JPME108View ArticleGoogle Scholar
- Quince C, Lanzen A, Davenport RJ, Turnbaugh PJ: Removing noise from pyrosequenced amplicons. BMC Bioinforma 2011, 12: 38–55. 10.1186/1471-2105-12-38View ArticleGoogle Scholar
- Rochelle PA, Cragg BA, Fry JC, Parkes RJ, Weightman AJ: Effect of sample handling on estimation of bacterial diversity in marine sediments by 16S rRNA gene sequence analysis. FEMS Microbiol Ecol 1994, 15: 215–225. 10.1111/j.1574-6941.1994.tb00245.xView ArticleGoogle Scholar
- Santegoeds CM, Damgaard LR, Hesselink G, Zopfi J, Lens P, Muyzer G, de Beer D: Distribution of sulfate-reducing and methanogenic bacteria in anaerobic aggregates determined by microsensor and molecular analysis. Appl Environ Microbiol 1999,65(10):4618–4629.PubMed CentralPubMedGoogle Scholar
- Schagat T, Koller S, Leone P, Cremonesi P, Bosetti A, Wieczorek D, Kephart D, Mann R, Storts D: The versatility of the Maxwell® 16 system for genomic DNA extraction. 2007. Promega Notes 97:12–14. Available viadocument. Accessed 07 November 2012 http://www.promega.com/resources/articles/pubhub/promega-notes-2007/the-versatility-of-the-maxwell-16-system-for-genomic-dna-extractionGoogle Scholar
- Schloss PD: Evaluating different approaches that test whether microbial communities have the same structure. ISME J 2008,2(3):265–275. 10.1038/ismej.2008.5View ArticlePubMedGoogle Scholar
- Schloss PD, Handelsman J: A statistical toolbox for metagenomics: assessing functional diversity in microbial communities. BMC Bioinforma 2008, 9: 34–48. 10.1186/1471-2105-9-34View ArticleGoogle Scholar
- Schloss PD, Westcott SL, Ryabin T, Hall JR, Hartmann M, Hollister EB, Lesniewski RA, Oakley BB, Parks DH, Robinson CJ, Sahl JW, Stres B, Thallinger GG, Van Horn DJ, Weber CF: Introducing mothur: open-source, platform-independent, community-supported software for describing and comparing microbial communities. Appl Environ Microbiol 2009,75(23):7537–7541. 10.1128/AEM.01541-09PubMed CentralView ArticlePubMedGoogle Scholar
- Schloss PD, Gevers D, Westcott SL: Reducing the effects of PCR amplification and sequencing artifacts on 16S rRNA-based studies. PLoS One 2011. 10.1371/journal.pone.0027310Google Scholar
- Shipley MA, Koehler JW, Kulesh DA, Minogue TD: Comparison of nucleic acid extraction platforms for detection of select biothreat agents for use in clinical resource limited settings. J Microbiol Methods J Microbiol Methods 2012,91(1):179–183.View ArticlePubMedGoogle Scholar
- Smith CJ, Osborn AM: Advantages and limitations of quantitative PCR (Q-PCR)-based approaches in microbial ecology. FEMS Microbiol Ecol 2009,67(1):6–20. 10.1111/j.1574-6941.2008.00629.xView ArticlePubMedGoogle Scholar
- Stach JE, Bathe S, Clapp JP, Burns RG: PCR-SSCP comparison of 16S rDNA sequence diversity in soil DNA obtained using different isolation and purification methods. FEMS Microbiol Ecol 2001, 36: 139–151. 10.1111/j.1574-6941.2001.tb00834.xView ArticlePubMedGoogle Scholar
- Stevenson BS, Drilling HS, Lawson PA, Duncan KE, Parisi VA, Suflita JM: Microbial communities in bulk fluids and biofilms of an oil facility have similar composition but different structure. Environ Microbiol 2011,13(4):1078–1090. 10.1111/j.1462-2920.2010.02413.xView ArticlePubMedGoogle Scholar
- Stults JR, Snoeyenbos-West O, Methe B, Lovley DR, Chandler DP: Application of the 5' fluorogenic exonuclease assay (TaqMan) for quantitative ribosomal DNA and rRNA analysis in sediments. Appl Environ Microbiol 2001,67(6):2781–2789. 10.1128/AEM.67.6.2781-2789.2001PubMed CentralView ArticlePubMedGoogle Scholar
- van der Kraan GM, Bruining J, Lomans BP, van Loosdrecht MC, Muyzer G: Microbial diversity of an oil–water processing site and its associated oil field: the possible role of microorganisms as information carriers from oil-associated environments. FEMS Microbiol Ecol 2010,71(3):428–443. 10.1111/j.1574-6941.2009.00813.xView ArticlePubMedGoogle Scholar
- van der Kraan GM, de Ridder M, Lomans BP, Muyzer G: Sampling and nucleic extraction procedures from oil reservoir samples. In Applied microbiology and molecular biology in oilfield systems. Edited by: Whitby C, Skovhus TL. Springer Science and Business Media LLC, New York; 2011.Google Scholar
- Wang Q, Garrity GM, Tiedje JM, Cole JR: Naive Bayesian classifier for rapid assignment of rRNA sequences into the new bacterial taxonomy. Appl Environ Microbiol 2007,73(16):5261–5267. 10.1128/AEM.00062-07PubMed CentralView ArticlePubMedGoogle Scholar
- Wawrik B, Mendivelso M, Parisi VA, Suflita JM, Davidova IA, Marks CR, Van Nostrand JD, Liang Y, Zhou J, Huizinga BJ, Strąpoć D, Callaghan AV: Field and laboratory studies on the bioconversion of coal to methane in the San Juan Basin. FEMS Microbiol Ecol 2011,81(1):26–42.View ArticleGoogle Scholar
- Wilson IG: Inhibition and facilitation of nucleic acid amplification. Appl Environ Microbiol 1997,63(10):3741–3751.PubMed CentralPubMedGoogle Scholar
- Zhou J, Wu L, Deng Y, Zhi X, Jiang YH, Tu Q, Xie J, Van Nostrand JD, He Z, Yang Y: Reproducibility and quantitation of amplicon sequencing-based detection. ISME J 2011,5(8):1303–1313. 10.1038/ismej.2011.11PubMed CentralView ArticlePubMedGoogle Scholar
This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.