Quantitative Tracing, by Taq Nuclease Assays, of a Synechococcus Ecotype in a Highly Diversified Natural Population

Quantitative Taq nuclease assays (TNAs) (TaqMan PCR), nested PCR in combination with denaturing gradient gel electrophoresis (DGGE), and epifluorescence microscopy were used to analyze the autotrophic picoplankton (APP) of Lake Constance. Microscopic analysis revealed dominance of phycoerythrin (PE)-rich Synechococcus spp. in the pelagic zone of this lake. Cells passing a 3-μm-pore-size filter were collected during the growth period of the years 1999 and 2000. The diversity of PE-rich Synechococcus spp. was examined using DGGE to analyze GC-clamped amplicons of a noncoding section of the 16S-23S intergenic spacer in the ribosomal operon. In both years, genotypes represented by three closely related PE-rich Synechococcus strains of our culture collection dominated the population, while other isolates were traced sporadically or were not detected in their original habitat by this method. For TNAs, primer-probe combinations for two taxonomic levels were used, one to quantify genomes of all known Synechococcus-type cyanobacteria in the APP of Lake Constance and one to enumerate genomes of a single ecotype represented by the PE-rich isolate Synechococcus sp. strain BO 8807. During the growth period, genome numbers of known Synechococcus spp. varied by 2 orders of magnitude (2.9 × 10³ to 3.1 × 10⁵ genomes per ml). The ecotype Synechococcus sp. strain BO 8807 was detected in every sample at concentrations between 1.6 × 10¹ and 1.3 × 10⁴ genomes per ml, contributing 0.02 to 5.7% of the quantified cyanobacterial picoplankton. Although the quantitative approach taken in this study has disclosed several shortcomings in the sampling and detection methods, this study demonstrated for the first time the extensive internal dynamics that lie beneath the seemingly arbitrary variations of a population of microbial photoautotrophs in the pelagic habitat.     

Interlaboratory comparison of Taq Nuclease Assays for the quantification of the toxic cyanobacteria Microcystis sp

The application of quantitative real-time PCR has been proposed for the quantification of toxic genotypes of cyanobacteria. We have compared the Taq Nuclease Assay (TNA) in quantifying the toxic cyanobacteria Microcystis sp. via the intergenic spacer region of the phycocyanin operon (PC) and mcyB indicative of the production of the toxic heptapeptide microcystin between three research groups employing three instruments (ABI7300, GeneAmp5700, ABI7500). The estimates of mcyB genotypes were compared using (i) DNA of a mcyB containing strain and a non-mcyB containing strain supplied in different mixtures across a low range of variation (0-10% of mcyB) and across a high range of variation (20-100%), and (ii) DNA from field samples containing Microcystis sp. For all three instruments highly significant linear regression curves between the proportion of the mcyB containing strain and the percentage of mcyB genotypes both within the low range and within the high range of mcyB variation were obtained. The regression curves derived from the three instruments differed in slope and within the high range of mcyB variation mcyB proportions were either underestimated (0-50%) or overestimated (0-72%). For field samples cell numbers estimated via both TNAs as well as mcyB proportions showed significant linear relationships between the instruments. For all instruments a linear relationship between the cell numbers estimated as PC genotypes and the cell numbers estimated as mcyB genotypes was observed. The proportions of mcyB varied from 2 to 28% and did not differ between the instruments. It is concluded that the TNA is able to provide quantitative estimates on mcyB genotype numbers that are reproducible between research groups and is useful to follow variation in mcyB genotype proportion occurring within weeks to months.     

Strain Identification and Quantitative Analysis in Microbial Communities

Microbiology has long studied the ways in which subtle genetic differences between closely related microbial strains can have profound impacts on their phenotypes and those of their surrounding environments and communities. Despite the growth in high-throughput microbial community profiling, however, such strain-level differences remain challenging to detect. Once detected, few quantitative approaches have been well-validated for associating strain variants from microbial communities with phenotypes of interest, such as medication usage, treatment efficacy, host environment, or health. First, the term “strain” itself is not used consistently when defining a highly-resolved taxonomic or genomic unit from within a microbial community. Second, computational methods for identifying such strains directly from shotgun metagenomics are difficult, with several possible reference- and assembly-based approaches available, each with different sensitivity/specificity tradeoffs. Finally, statistical challenges exist in using any of the resulting strain profiles for downstream analyses, which can include strain tracking, phylogenetic analysis, or genetic association studies. We provide an in depth discussion of recently available computational tools that can be applied for this task, as well as statistical models and gaps in performing and interpreting any of these three main types of studies using strain-resolved shotgun metagenomic profiling of microbial communities.     

Assessment of Soil Microbial Community Structure by Use of Taxon-Specific Quantitative PCR Assays

Here we describe a quantitative PCR-based approach to estimating the relative abundances of major taxonomic groups of bacteria and fungi in soil. Primers were thoroughly tested for specificity, and the method was applied to three distinct soils. The technique provides a rapid and robust index of microbial community structure.     

Terminal Restriction Fragment Length Polymorphism Data Analysis for Quantitative Comparison of Microbial Communities

Terminal restriction fragment length polymorphism (T-RFLP) is a culture-independent method of obtaining a genetic fingerprint of the composition of a microbial community. Comparisons of the utility of different methods of (i) including peaks, (ii) computing the difference (or distance) between profiles, and (iii) performing statistical analysis were made by using replicated profiles of eubacterial communities. These samples included soil collected from three regions of the United States, soil fractions derived from three agronomic field treatments, soil samples taken from within one meter of each other in an alfalfa field, and replicate laboratory bioreactors. Cluster analysis by Ward's method and by the unweighted-pair group method using arithmetic averages (UPGMA) were compared. Ward's method was more effective at differentiating major groups within sets of profiles; UPGMA had a slightly reduced error rate in clustering of replicate profiles and was more sensitive to outliers. Most replicate profiles were clustered together when relative peak height or Hellinger-transformed peak height was used, in contrast to raw peak height. Redundancy analysis was more effective than cluster analysis at detecting differences between similar samples. Redundancy analysis using Hellinger distance was more sensitive than that using Euclidean distance between relative peak height profiles. Analysis of Jaccard distance between profiles, which considers only the presence or absence of a terminal restriction fragment, was the most sensitive in redundancy analysis, and was equally sensitive in cluster analysis, if all profiles had cumulative peak heights greater than 10,000 fluorescence units. It is concluded that T-RFLP is a sensitive method of differentiating between microbial communities when the optimal statistical method is used for the situation at hand. It is recommended that hypothesis testing be performed by redundancy analysis of Hellinger-transformed data and that exploratory data analysis be performed by cluster analysis using Ward's method to find natural groups or by UPGMA to identify potential outliers. Analyses can also be based on Jaccard distance if all profiles have cumulative peak heights greater than 10,000 fluorescence units.     

Assessing the Performance Capabilities of LRE-Based Assays for Absolute Quantitative Real-Time PCR

Background

Linear regression of efficiency or LRE introduced a new paradigm for conducting absolute quantification, which does not require standard curves, can generate absolute accuracies of ±25% and has single molecule sensitivity. Derived from adapting the classic Boltzmann sigmoidal function to PCR, target quantity is calculated directly from the fluorescence readings within the central region of an amplification profile, generating 4–8 determinations from each amplification reaction.

Findings

Based on generating a linear representation of PCR amplification, the highly visual nature of LRE analysis is illustrated by varying reaction volume and amplification efficiency, which also demonstrates how LRE can be used to model PCR. Examining the dynamic range of LRE further demonstrates that quantitative accuracy can be maintained down to a single target molecule, and that target quantification below ten molecules conforms to that predicted by Poisson distribution. Essential to the universality of optical calibration, the fluorescence intensity generated by SYBR Green I (FU/bp) is shown to be independent of GC content and amplicon size, further verifying that absolute scale can be established using a single quantitative standard. Two high-performance lambda amplicons are also introduced that in addition to producing highly precise optical calibrations, can be used as benchmarks for performance testing. The utility of limiting dilution assay for conducting platform-independent absolute quantification is also discussed, along with the utility of defining assay performance in terms of absolute accuracy.

Conclusions

Founded on the ability to exploit lambda gDNA as a universal quantitative standard, LRE provides the ability to conduct absolute quantification using few resources beyond those needed for sample preparation and amplification. Combined with the quantitative and quality control capabilities of LRE, this kinetic-based approach has the potential to fundamentally transform how real-time qPCR is conducted.     

Quantitative Molecular Assay for Fingerprinting Microbial Communities of Wastewater and Estrogen-Degrading Consortia

A quantitative fingerprinting method, called the real-time terminal restriction fragment length polymorphism (real-time-t-RFLP) assay, was developed for simultaneous determination of microbial diversity and abundance within a complex community. The real-time-t-RFLP assay was developed by incorporating the quantitative feature of real-time PCR and the fingerprinting feature of t-RFLP analysis. The assay was validated by using a model microbial community containing three pure strains, an Escherichia coli strain (gram negative), a Pseudomonas fluorescens strain (gram negative), and a Bacillus thuringiensis strain (gram positive). Subsequently, the real-time-t-RFLP assay was applied to and proven to be useful for environmental samples; the richness and abundance of species in microbial communities (expressed as the number of 16S rRNA gene copies of each ribotype per milliliter) of wastewater and estrogen-degrading consortia (enriched with 17α-estradiol, 17β-estradiol, or estrone) were successfully characterized. The results of this study strongly suggested that the real-time-t-RFLP assay can be a powerful molecular tool for gaining insight into microbial communities in various engineered systems and natural habitats.     

Comparison of Two Quantitative Real Time PCR Assays for Rickettsia Detection in Patients from Tunisia

Background and objectives

Quantitative real time PCR (qPCR) offers rapid diagnosis of rickettsial infections. Thus, successful treatment could be initiated to avoid unfavorable outcome. Our aim was to compare two qPCR assays for Rickettsia detection and to evaluate their contribution in early diagnosis of rickettsial infection in Tunisian patients.

Patients and methods

Included patients were hospitalized in different hospitals in Tunisia from 2007 to 2012. Serology was performed by microimmunofluorescence assay using R. conorii and R. typhi antigens. Two duplex qPCRs, previously reported, were performed on collected skin biopsies and whole blood samples. The first duplex amplified all Rickettsia species (PanRick) and Rickettsia typhi DNA (Rtt). The second duplex detected spotted fever group Rickettsiae (RC00338) and typhus group Rickettsiae DNA (Rp278).

Results

Diagnosis of rickettsiosis was confirmed in 82 cases (57.7%). Among 44 skin biopsies obtained from patients with confirmed diagnosis, the first duplex was positive in 24 samples (54.5%), with three patients positive by Rtt qPCR. Using the second duplex, positivity was noted in 21 samples (47.7%), with two patients positive by Rp278 qPCR. Among79 whole blood samples obtained from patients with confirmed diagnosis, panRick qPCR was positive in 5 cases (6.3%) among which two were positive by Rtt qPCR. Using the second set of qPCRs, positivity was noted in four cases (5%) with one sample positive by Rp278 qPCR. Positivity rates of the two duplex qPCRs were significantly higher among patients presenting with negative first serum than those with already detectable antibodies.

Conclusions

Using qPCR offers a rapid diagnosis. The PanRick qPCR showed a higher sensitivity. Our study showed that this qPCR could offer a prompt diagnosis at the early stage of the disease. However, its implementation in routine needs cost/effectiveness evaluation.     

Quantitative Analysis of Small-Subunit rRNA Genes in Mixed Microbial Populations via 5′-Nuclease Assays

Few techniques are currently available for quantifying specific prokaryotic taxa in environmental samples. Quantification of specific genotypes has relied mainly on oligonucleotide hybridization to extracted rRNA or intact rRNA in whole cells. However, low abundance and cellular rRNA content limit the application of these techniques in aquatic environments. In this study, we applied a newly developed quantitative PCR assay (5′-nuclease assay, also known as TaqMan) to quantify specific small-subunit (SSU) rRNA genes (rDNAs) from uncultivated planktonic prokaryotes in Monterey Bay. Primer and probe combinations for quantification of SSU rDNAs at the domain and group levels were developed and tested for specificity and quantitative reliability. We examined the spatial and temporal variations of SSU rDNAs from Synechococcus plus Prochlorococcus and marine Archaea and compared the results of the quantitative PCR assays to those obtained by alternative methods. The 5′-nuclease assays reliably quantified rDNAs over at least 4 orders of magnitude and accurately measured the proportions of genes in artificial mixtures. The spatial and temporal distributions of planktonic microbial groups measured by the 5′-nuclease assays were similar to the distributions estimated by quantitative oligonucleotide probe hybridization, whole-cell hybridization assays, and flow cytometry.     

Quantitative Real-Time PCR Assays for Sensitive Detection of Canada Goose-Specific Fecal Pollution in Water Sources

Canada geese (Branta canadensis) are prevalent in North America and may contribute to fecal pollution of water systems where they congregate. This work provides two novel real-time PCR assays (CGOF1-Bac and CGOF2-Bac) allowing for the specific and sensitive detection of Bacteroides 16S rRNA gene markers present within Canada goose feces.The Canada goose (Branta canadensis) is a prevalent waterfowl species in North America. The population density of Canada geese has doubled during the past 15 years, and the population was estimated to be close to 3 million in 2007 (4). Canada geese often congregate within urban settings, likely due to available water sources, predator-free grasslands, and readily available food supplied by humans (6). They are suspected to contribute to pollution of aquatic environments due to the large amounts of fecal matter that can be transported into the water. This can create a public health threat if the fecal droppings contain pathogenic microorganisms (6, 7, 9, 10, 12, 13, 19). Therefore, tracking transient fecal pollution of water due to fecal inputs from waterfowl, such as Canada geese, is of importance for protecting public health.PCR detection of host-specific 16S rRNA gene sequences from Bacteroidales of fecal origin has been described as a promising microbial source-tracking (MST) approach due to its rapidity and high specificity (2, 3). Recently, Lu et al. (15) characterized the fecal microbial community from Canada geese by constructing a 16S rRNA gene sequence database using primers designed to amplify all bacterial 16S rRNA gene sequences. The authors reported that the majority of the 16S rRNA gene sequences obtained were related to Clostridia or Bacilli and to a lesser degree Bacteroidetes, which represent possible targets for host-specific source-tracking assays.The main objective of this study was to identify novel Bacteroidales 16S rRNA gene sequences that are specific to Canada goose feces and design primers and TaqMan fluorescent probes for sensitive and specific quantification of Canada goose fecal contamination in water sources.Primers 32F and 708R from Bernhard and Field (2) were used to construct a Bacteroidales-specific 16S rRNA gene clone library from Canada goose fecal samples (n = 15) collected from grass lawns surrounding Wascana Lake (Regina, SK, Canada) in May 2009 (for a detailed protocol, see File S1 in the supplemental material). Two hundred eighty-eight clones were randomly selected and subjected to DNA sequencing (at the Plant Biotechnology Institute DNA Technologies Unit, Saskatoon, SK, Canada). Representative sequences of each operational taxonomic unit (OTU) were recovered using an approach similar to that described by Mieszkin et al. (16). Sequences that were less than 93% similar to 16S rRNA gene sequences from nontarget host species in GenBank were used in multiple alignments to identify regions of DNA sequence that were putatively goose specific. Subsequently, two TaqMan fluorescent probe sets (targeting markers designated CGOF1-Bac and CGOF2-Bac) were designed using the RealTimeDesign software provided by Biosearch Technologies (http://www.biosearchtech.com/). The newly designed primer and probe set for the CGOF1-Bac assay included CG1F (5′-GTAGGCCGTGTTTTAAGTCAGC-3′) and CG1R (5′-AGTTCCGCCTGCCTTGTCTA-3′) and a TaqMan probe (5′-6-carboxyfluorescein [FAM]-CCGTGCCGTTATACTGAGACACTTGAG-Black Hole Quencher 1 [BHQ-1]-3′), and the CGOF2-Bac assay had primers CG2F (5′-ACTCAGGGATAGCCTTTCGA-3′) and CG2R (5′-ACCGATGAATCTTTCTTTGTCTCC-3′) and a TaqMan probe (5′-FAM-AATACCTGATGCCTTTGTTTCCCTGCA-BHQ-1-3′). Oligonucleotide specificities for the Canada goose-associated Bacteroides 16S rRNA primers were verified through in silico analysis using BLASTN (1) and the probe match program of the Ribosomal Database Project (release 10) (5). Host specificity was further confirmed using DNA extracts from 6 raw human sewage samples from various geographical locations in Saskatchewan and 386 fecal samples originating from 17 different animal species in Saskatchewan, including samples from Canada geese (n = 101) (Table ​(Table1).1). An existing nested PCR assay for detecting Canada goose feces (15) (targeting genetic marker CG-Prev f5) (see Table S1 in the supplemental material) was also tested for specificity using the individual fecal and raw sewage samples (Table ​(Table1).1). All fecal DNA extracts were obtained from 0.25 g of fecal material by using the PowerSoil DNA extraction kit (Mo Bio Inc., Carlsbad, CA) (File S1 in the supplemental material provides details on the sample collection).

TABLE 1.

Specificities of the CGOF1-Bac, CGOF2-Bac, and CG-Prev f5 PCR assays for different species present in Saskatchewan, Canada

Edesign: Primer and Enhanced Internal Probe Design Tool for Quantitative PCR Experiments and Genotyping Assays

Analytical PCR experiments preferably use internal probes for monitoring the amplification reaction and specific detection of the amplicon. Such internal probes have to be designed in close context with the amplification primers, and may require additional considerations for the detection of genetic variations. Here we describe Edesign, a new online and stand-alone tool for designing sets of PCR primers together with an internal probe for conducting quantitative real-time PCR (qPCR) and genotypic experiments. Edesign can be used for selecting standard DNA oligonucleotides like for instance TaqMan probes, but has been further extended with new functions and enhanced design features for Eprobes. Eprobes, with their single thiazole orange-labelled nucleotide, allow for highly sensitive genotypic assays because of their higher DNA binding affinity as compared to standard DNA oligonucleotides. Using new thermodynamic parameters, Edesign considers unique features of Eprobes during primer and probe design for establishing qPCR experiments and genotyping by melting curve analysis. Additional functions in Edesign allow probe design for effective discrimination between wild-type sequences and genetic variations either using standard DNA oligonucleotides or Eprobes. Edesign can be freely accessed online at http://www.dnaform.com/edesign2/, and the source code is available for download.     

Cold-sensitive mutants of Taq DNA polymerase provide a hot start for PCR

Although the thermophilic bacterium Thermus aquaticus grows optimally at 70°C and cannot grow at moderate temperatures, its DNA polymerase I has significant activity at 20–37°C. This activity is a bane to some PCRs, since it catalyzes non-specific priming. We report mutations of Klentaq (an N-terminal deletion variant) DNA polymerase that have markedly reduced activity at 37°C yet retain apparently normal activity at 68°C and resistance at 95°C. The first four of these mutations are clustered on the outside surface of the enzyme, nowhere near the active site, but at the hinge point of a domain that has been proposed to move at each cycle of nucleotide incorporation. We show that the novel cold-sensitive mutants can provide a hot start for PCR and exhibit slightly improved fidelity.     

UniFrac: a New Phylogenetic Method for Comparing Microbial Communities

We introduce here a new method for computing differences between microbial communities based on phylogenetic information. This method, UniFrac, measures the phylogenetic distance between sets of taxa in a phylogenetic tree as the fraction of the branch length of the tree that leads to descendants from either one environment or the other, but not both. UniFrac can be used to determine whether communities are significantly different, to compare many communities simultaneously using clustering and ordination techniques, and to measure the relative contributions of different factors, such as chemistry and geography, to similarities between samples. We demonstrate the utility of UniFrac by applying it to published 16S rRNA gene libraries from cultured isolates and environmental clones of bacteria in marine sediment, water, and ice. Our results reveal that (i) cultured isolates from ice, water, and sediment resemble each other and environmental clone sequences from sea ice, but not environmental clone sequences from sediment and water; (ii) the geographical location does not correlate strongly with bacterial community differences in ice and sediment from the Arctic and Antarctic; and (iii) bacterial communities differ between terrestrially impacted seawater (whether polar or temperate) and warm oligotrophic seawater, whereas those in individual seawater samples are not more similar to each other than to those in sediment or ice samples. These results illustrate that UniFrac provides a new way of characterizing microbial communities, using the wealth of environmental rRNA sequences, and allows quantitative insight into the factors that underlie the distribution of lineages among environments.     

Quantitative Consideration of Ecosystem Characteristics in an Ecological Risk Assessment: A Case Study

Development of assessment endpoints and conceptual models aids ecological risk assessors in identifying measurable attributes that will allow quantification and prediction of risk. Measures of exposure and effect are explicitly considered, usually quantitatively, in nearly every ecological risk assessment, while measures of ecosystem characteristics are generally addressed only implicitly, if at all. Yet these characteristics influence both the behavior and location of assessment endpoint entities and the spatial and temporal distribution of stressors. This case study illustrates use of a regression partitioning model to quantify the influence of ecosystem characteristics (e.g., land use patterns, nutrient concentrations) on the concentration of a chemical stressor (atrazine) in surface waters of a large river basin. The model partitioned the basin into five land use groups ranging from High Forested to Very High Agriculture. Literature-derived chronic effects data were used with a joint-probability model to characterize atrazine risk to an aquatic assessment entity in each of these land use subgroups. Atrazine concentrations and risk directly correlated with the intensity of agricultural land use. This permits risk management to focus on agricultural areas within the basin; a focus that would not have been possible without explicitly considering ecosystem characteristics.     

Microscale Analyses of the Formation and Nature of Microbial Biofilm Communities in River Systems

The review covers aspects of biofilm cultivation, laser scanning microscopy, molecular probes and digital image analyses. This is accomplished through an overview of selected studies which illustrate the application of the microscale approach and laser microscopy techniques to the study of river biofilms and the results obtained.     

Comparison of Quantitative PCR and Droplet Digital PCR Multiplex Assays for Two Genera of Bloom-Forming Cyanobacteria,Cylindrospermopsis and Microcystis

The increasing occurrence of harmful cyanobacterial blooms, often linked to deteriorated water quality and adverse public health effects, has become a worldwide concern in recent decades. The use of molecular techniques such as real-time quantitative PCR (qPCR) has become increasingly popular in the detection and monitoring of harmful cyanobacterial species. Multiplex qPCR assays that quantify several toxigenic cyanobacterial species have been established previously; however, there is no molecular assay that detects several bloom-forming species simultaneously. Microcystis and Cylindrospermopsis are the two most commonly found genera and are known to be able to produce microcystin and cylindrospermopsin hepatotoxins. In this study, we designed primers and probes which enable quantification of these genera based on the RNA polymerase C1 gene for Cylindrospermopsis species and the c-phycocyanin beta subunit-like gene for Microcystis species. Duplex assays were developed for two molecular techniques—qPCR and droplet digital PCR (ddPCR). After optimization, both qPCR and ddPCR assays have high linearity and quantitative correlations for standards. Comparisons of the two techniques showed that qPCR has higher sensitivity, a wider linear dynamic range, and shorter analysis time and that it was more cost-effective, making it a suitable method for initial screening. However, the ddPCR approach has lower variability and was able to handle the PCR inhibition and competitive effects found in duplex assays, thus providing more precise and accurate analysis for bloom samples.