Absolute Quantification of Enterococcal 23S rRNA Gene Using Digital

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Absolute Quantification of Enterococcal 23S rRNA Gene Using Digital PCR Dan Wang, Kevan M Yamahara, Yiping Cao, and Alexandria B. Boehm Environ. Sci. Technol., Just Accepted Manuscript • DOI: 10.1021/acs.est.5b05747 • Publication Date (Web): 22 Feb 2016 Downloaded from http://pubs.acs.org on February 28, 2016

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Environmental Science & Technology

Figure 1. The impact of gDNA fragmentation on the positive counts reported by dPCR. The error bars represent the Poisson 95% confidence interval resulted from 15,000-22,000 partitions per dPCR chip. (A1, gDNA extracted by Qiagen DNeasy blood and tissue kit for Gram-positive bacteria; A2, over-digested of A1 by HindIII B1 ~ B4, gDNA extracted by GeneRite DNA-EZ ST1 kit, for 1min (B1), 2.5 min (B2), 5 min (B3) and 10 min (B4) beadbeating, respectively). 114x79mm (300 x 300 DPI)

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Figure 2. dPCR quantification against nominal concentration derived from Qubit quantification. Error bars represent the Poisson 95% confidence interval for dPCR quantification. 85x79mm (300 x 300 DPI)


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Figure 3 qPCR and dPCR quantification for 24 environmental samples. Error bars represent the 95% confidence interval. Solid line is the linear regression line with zero intercept between qPCR and dPCR measurements. 105x100mm (300 x 300 DPI)



Figure 4. The inhibitive effect of humic acid and calcium on qPCR (40 cycles reaction) and dPCR (45 cycles reaction). Error bars represent the 95% confidence interval. 155x141mm (300 x 300 DPI)


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Figure 5. Impact of thermal cycle numbers on dPCR quantification under influence of 5 ng/µl humic acid or 2 mM of calcium. Error bars represent the Poisson 95% confidence interval. 78x36mm (300 x 300 DPI)



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Absolute Quantification of Enterococcal 23S rRNA Gene Using Digital PCR

2 3

Dan Wang1,3*, Kevan M. Yamahara1, Yiping Cao2, Alexandria B. Boehm1,

4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38

1. Environmental and Water Studies, Department of Civil and Environmental Engineering, Stanford University, CA 94305, USA. 2. Southern California Coastal Water Research Project Authority, Costa Mesa, CA 92626, USA 3. Current address: California Department of Pesticide Regulation, Sacramento, CA 95812, USA

A manuscript for Environmental Science & Technology

*Corresponding author contact information: 1001 I Street, Sacramento, CA 95812. Phone: 916-324-4201. Email: [email protected].


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ABSTRACT

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We evaluated the ability of chip-based digital PCR (dPCR) to quantify enterococci, the

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fecal indicator recommended by USEPA for water quality monitoring. dPCR uses

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Poisson statistics to estimate the number of DNA fragments in a sample with a specific

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sequence. Underestimation may occur when a gene is redundantly encoded in the genome

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and multiple copies of that gene are on one DNA fragment. When genomic DNA (gDNA)

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was extracted using two commercial DNA extraction kits, we confirmed that dPCR could

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discern individual copies of the redundant 23s rRNA gene in the enterococcal genome.

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dPCR quantification was accurate when compared to the nominal concentration inferred

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from fluorometer measurements (linear regression slope=0.98, intercept =0.03, R2 =0.99,

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and p-value < 0.0001). dPCR quantification was also consistent with quantitative PCR

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(qPCR) measurements as well as cell counts for BioBall® reference standard and 24

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environmental water samples. qPCR and dPCR quantification of enterococci in the 24

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environmental samples were significantly correlated (linear regression slope = 1.08, R2 of

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0.96, and p-value 18 h later); therefore, rapid detection technologies with shorter sample-to-

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result time are necessary to adequately protect public health.3-5 In 2012, the United States

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Environmental Protection Agency (USEPA) published new recreational water quality

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criteria that included numerical limits for enterococci enumerated using qPCR following

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USEPA Method 16116 or other related qPCR methods.7 Thus, US laboratories

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performing routine water quality monitoring have the option to enumerate enterococci

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using qPCR.

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Several limitations of qPCR have been reported that affect its ability to produce

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accurate and consistent measurements across and within laboratories.8, 9 Quantification

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via qPCR is relative; it is based on standard curves constructed from reference material

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such as genomic DNA (gDNA), plasmid DNA, or synthesized DNA fragments.

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Therefore, it requires careful calibration via the standard curve10, 11 and standardization of

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the reference material across laboratories.12 Using a standard curve to accurately quantify

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qPCR targets requires that the PCR amplification efficiency of target DNA in the

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environmental samples be identical to the amplification efficiency of the reference

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material. This requirement presents a challenge, as many environmental samples contain

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PCR inhibitors that affect amplification efficiency.13, 14


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Digital PCR (dPCR) is a relatively new PCR technology that allows absolute

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quantification of nucleic acids.15 In dPCR, the PCR mixture (typically 10-50 µl in volume)

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is partitioned into many small individual reactions (typically 0.5-1.0 nl in volume). The

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number of partitions needs to be large enough in order to separate individual copies of the

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target sequences into different reactions; therefore, the number of partitions that are PCR-

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positive reflects the copy numbers of the target sequence. Based on Poisson statistics, this

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practice will ensure that the predominant of the individual partitions contain zero or one

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copy of the target sequence (Poisson parameter λ should be

Absolute Quantification of Enterococcal 23S rRNA Gene Using Digital

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