Winter Ciliates in a British Columbian Fjord: Six New Species and an Analysis of Ciliate Putative Prey

ABSTRACT. This work provides the first study of North Pacific planktonic ciliates by quantitative protargol staining. Triplicate water bottle samples were collected at a depth of 2 m (above the shallow pycnocline) at six stations in Indian Arm, British Columbia, on February 15, 1990, and February 26, 1991. Thirty-six ciliate species were observed. Six new species are described from protargolstained specimens: Strombidium lynni n. sp., Strombidium taylori n. sp., Strombidium basimorphum n. sp., Slrombidiurn ventropinnum n. sp., Strobilidium undinum n. sp., and Urotricha cyrtonucleata n. sp.
Ciliate abundance varied significantly (ANOVA, α= 0.05) between sampling sites, ranging from 550 to 6,800 cells/liter in 1990 and from 1,800 to 7,900 cells/liter in 1991. Biomass also varied significantly (ANOVA, α= 0.05) ranging from 3.7 × 10⁵ to 3.3 × 10⁶ pg carbon/liter in 1990 and 3.04 × 10⁶− 6.97 × 10⁶ pg carbon/liter in 1991. Putative prey were enumerated in three size fractions (1.5–5 μm, 5–10 μm and 10–25 μm). The source of variation in ciliate abundance and biomass was not identified. Parameters of salinity, temperature, putative prey, chlorophyll a and pycnocline depth did not significantly correlate with ciliate biomass or abundance (α= 0.05).     

Weed Mapping in Early-Season Maize Fields Using Object-Based Analysis of Unmanned Aerial Vehicle (UAV) Images

The use of remote imagery captured by unmanned aerial vehicles (UAV) has tremendous potential for designing detailed site-specific weed control treatments in early post-emergence, which have not possible previously with conventional airborne or satellite images. A robust and entirely automatic object-based image analysis (OBIA) procedure was developed on a series of UAV images using a six-band multispectral camera (visible and near-infrared range) with the ultimate objective of generating a weed map in an experimental maize field in Spain. The OBIA procedure combines several contextual, hierarchical and object-based features and consists of three consecutive phases: 1) classification of crop rows by application of a dynamic and auto-adaptive classification approach, 2) discrimination of crops and weeds on the basis of their relative positions with reference to the crop rows, and 3) generation of a weed infestation map in a grid structure. The estimation of weed coverage from the image analysis yielded satisfactory results. The relationship of estimated versus observed weed densities had a coefficient of determination of r²=0.89 and a root mean square error of 0.02. A map of three categories of weed coverage was produced with 86% of overall accuracy. In the experimental field, the area free of weeds was 23%, and the area with low weed coverage (<5% weeds) was 47%, which indicated a high potential for reducing herbicide application or other weed operations. The OBIA procedure computes multiple data and statistics derived from the classification outputs, which permits calculation of herbicide requirements and estimation of the overall cost of weed management operations in advance.     

Microbial Life in a Fjord: Metagenomic Analysis of a Microbial Mat in Chilean Patagonia

The current study describes the taxonomic and functional composition of metagenomic sequences obtained from a filamentous microbial mat isolated from the Comau fjord, located in the northernmost part of the Chilean Patagonia. The taxonomic composition of the microbial community showed a high proportion of members of the Gammaproteobacteria, including a high number of sequences that were recruited to the genomes of Moritella marina MP-1 and Colwellia psycherythraea 34H, suggesting the presence of populations related to these two psychrophilic bacterial species. Functional analysis of the community indicated a high proportion of genes coding for the transport and metabolism of amino acids, as well as in energy production. Among the energy production functions, we found protein-coding genes for sulfate and nitrate reduction, both processes associated with Gammaproteobacteria-related sequences. This report provides the first examination of the taxonomic composition and genetic diversity associated with these conspicuous microbial mat communities and provides a framework for future microbial studies in the Comau fjord.     

Accurate Quantification of Microorganisms in PCR-Inhibiting Environmental DNA Extracts by a Novel Internal Amplification Control Approach Using Biotrove OpenArrays

PCR-based detection assays are prone to inhibition by substances present in environmental samples, thereby potentially leading to inaccurate target quantification or false-negative results. Internal amplification controls (IACs) have been developed to help alleviate this problem but are generally applied in a single concentration, thereby yielding less-than-optimal results across the wide range of microbial gene target concentrations possible in environmental samples (J. Hoorfar, B. Malorny, A. Abdulmawjood, N. Cook, M. Wagner, and P. Fach, J. Clin. Microbiol. 42:1863-1868, 2004). Increasing the number of IACs for each quantitative PCR (qPCR) sample individually, however, typically reduces sensitivity and, more importantly, the reliability of quantification. Fortunately, current advances in high-throughput qPCR platforms offer the possibility of multiple reactions for a single sample simultaneously, thereby allowing the implementation of more than one IAC concentration per sample. Here, we describe the development of a novel IAC approach that is specifically designed for the state-of-the-art Biotrove OpenArray platform. Different IAC targets were applied at a range of concentrations, yielding a calibration IAC curve for each individual DNA sample. The developed IACs were optimized, tested, and validated by using more than 5,000 unique qPCR amplifications, allowing accurate quantification of microorganisms when applied to soil DNA extracts containing various levels of PCR-inhibiting compounds. To our knowledge, this is the first study using a suite of IACs at different target concentrations to monitor PCR inhibition across a wide target range, thereby allowing reliable and accurate quantification of microorganisms in PCR-inhibiting DNA extracts. The developed IAC is ideally suited for high-throughput screenings of, for example, ecological and agricultural samples on next-generation qPCR platforms.Real-time PCR-based nucleic acid amplification is currently the most commonly used strategy for the quantification of microorganisms and specific gene expression in environmental samples. Such PCR-based nucleic acid amplification is sensitive, accurate, and relatively fast and allows the detection, cultivation-independent identification, and quantification of microorganisms.Despite the advantages of PCR-based assays, one major drawback is potential inhibition of the amplification reaction by compounds that are often coextracted with nucleic acids from the sample matrix (9, 14, 26, 30). Therefore, much research has been directed toward the development of optimized DNA extraction protocols for difficult environmental samples (1, 2, 8, 18, 21, 23, 24, 27, 31, 32). Nevertheless, coextraction of PCR-inhibiting compounds often cannot be completely prevented, thereby potentially leading to false-negative results (4, 5, 7, 13). Moreover, the occurrence of partial PCR inhibition can lead to inaccurate target quantification, thereby underestimating the true number of assayed targets present in the sample (26).A straightforward approach to detect PCR inhibition is the inclusion of an internal amplification control (IAC) (6, 7, 16, 28). An IAC is a nontarget DNA sequence that is coamplified with the target under the same reaction conditions and in the same reaction tube. Most currently used IACs can be divided into two distinct groups: competitive and noncompetitive IACs (7). In competitive IACs, the target and IAC are amplified with the same primer set. In noncompetitive IACs, both the target and IAC are amplified with different primer sets (7). In such strategies, however, competition between the IAC and the target DNA for primers (competitive IAC), nucleotides, and polymerase enzymes (competitive and noncompetitive IAC) can occur (7, 11, 12). Although the absence or presence of a target (qualitative detection) can usually be determined unambiguously after proper optimization via both IAC strategies, the competition for reaction components makes accurate quantification problematic. Therefore, to allow accurate adjustments to quantitative data in the case of partial PCR inhibition, separate reactions for each target and (noncompetitive) IAC should be performed. A drawback of this approach is the resulting dramatic increase in the number of reactions that have to be performed, which is of particular concern when large-scale screening of samples is required or in cases where only a small amount of template DNA is available.A solution to this problem was offered by the recent development of next-generation quantitative PCR (qPCR) platforms like the Biotrove OpenArray system. This novel qPCR platform provides high-density and low-volume qPCR microarrays that are capable of accommodating 3,072 reactions per array (OpenArray; BioTrove Inc., Woburn, MA) (15, 25, 29). The OpenArray contains 48 subarrays, each consisting of 64 microscopic through holes with a volume of 33 nl (Fig. ​(Fig.1A)1A) into which primer pairs are preloaded as specified by the user. Depending on the assay layout, a single OpenArray allows parallel testing of up to 144 samples against a maximum of 3,072 targets.Open in a separate windowFIG. 1.Schematic overview of the internal amplification control (IAC) on the Biotrove OpenArray system. (A) OpenArray architecture. The OpenArray has 48 subarrays, each containing 64 microscopic 33-nl through holes. The primers are preloaded into the holes. The sample combined with the reaction mixture is autoloaded by the surface tension of the hydrophilically coated holes and the hydrophobic surface of the OpenArray. (B) IAC target design. Each IAC target consists of a 60-nucleotide-long spacer DNA fragment (S1, S2, S3, S4) flanked by IAC-unique primer sequences (F1/R1, F2/R2, F3/R3, F4/R4). The sequence order of the spacer DNA fragments is randomized for each IAC, but all of the IACs are equal in nucleotide composition. The IAC-unique primer pairs ensure IAC-specific amplification in a real-time PCR. IAC targets were cloned into pGem-T vectors. (C) IAC detection principle. A mixture containing a range of concentrations of the four IAC targets, the DNA sample, and real-time PCR reagents is loaded onto a subarray. The IAC targets are independently amplified with the IAC-unique primers which are spotted into selected through holes. Amplification is monitored with SYBR green dye, and potential PCR inhibition is assessed based on the C_T numbers of the IAC target mixture.To date, most IACs have been applied in a single concentration. It has, however, been shown that IACs used at high concentrations may fail to detect weak PCR inhibition and that inhibition of target amplification may be target concentration dependent (7, 22). Here, we hypothesized that accurate quantification by real-time PCR requires an IAC with a wider concentration range. Fortunately, new-generation qPCR platforms facilitated the development of such a new type of amplification control without increased labor or cost.In this report, we describe a newly developed IAC approach in which different IAC targets are applied at a range of concentrations, thereby providing a calibration IAC curve that enables more accurate target quantification. Primers for the different IACs are spotted along with target-specific primer pairs in separate through holes per subarray, while the IAC target mixture is spiked into the environmental DNA extracts (Fig. 1B and C). The DNA-IAC mixture is then loaded onto the OpenArray subarray, and all targets are amplified and monitored individually in real time (Fig. ​(Fig.1C1C).We describe the development, testing, and application of a novel IAC approach for high-throughput screening of environmental samples on next-generation qPCR platforms. Soil DNA extracts varying in their degrees of PCR inhibition were used to demonstrate that this IAC strategy can accurately compensate for partial PCR inhibition during the detection of microbial targets in complex environmental samples. The benefits of our novel IAC approach are discussed with respect its application to various complex matrices where accurate quantification of targets is desired.     

Quantification of Tartrate Resistant Acid Phosphatase Activity Using a Computerized Image Analysis System

Tartrate resistant acid phosphatase (TRAP) has been accepted as a marker for identification of osteoclasts. A method is reported here for quantitating TRAP using an image analysis system. The amount of the enzyme specific to osteoclasts can be used to differentiate osteoclasts from other cells capable of TRAP expression. TRAP expression characteristic of the osteoclast was compared with that of multinucleated giant cells (MNGC)s recruited to the site of subcutaneously implanted mineralized bone matrix. Two weeks post-implantation, the pellets were removed and processed for the demonstration of TRAP along with rat proximal tibiae. A large amount of TRAP was consistently expressed by the in situ osteoclasts. The MNGCs associated with the mineralized bone implants expressed little if any TRAP reaction product. Using this system, the amount of TRAP reaction product or any other enzyme reaction product expressed can be objectively and reproducibly quantitated.     

Quantification of Tartrate Resistant Acid Phosphatase Activity Using a Computerized Image Analysis System

Tartrate resistant acid phosphatase (TRAP) has been accepted as a marker for identification of osteoclasts. A method is reported here for quantitating TRAP using an image analysis system. The amount of the enzyme specific to osteoclasts can be used to differentiate osteoclasts from other cells capable of TRAP expression. TRAP expression characteristic of the osteoclast was compared with that of multinucleated giant cells (MNGC)s recruited to the site of subcutaneously implanted mineralized bone matrix. Two weeks post-implantation, the pellets were removed and processed for the demonstration of TRAP along with rat proximal tibiae. A large amount of TRAP was consistently expressed by the in situ osteoclasts. The MNGCs associated with the mineralized bone implants expressed little if any TRAP reaction product. Using this system, the amount of TRAP reaction product or any other enzyme reaction product expressed can be objectively and reproducibly quantitated.     

Quantification of Rat Kisspeptin Using a Novel Radioimmunoassay

Kisspeptin is a hypothalamic peptide hormone that plays a pivotal role in pubertal onset and reproductive function. Previous studies have examined hypothalamic kisspeptin mRNA expression, either through in situ hybridisation or real-time RT-PCR, as a means quantifying kisspeptin gene expression. However, mRNA expression levels are not always reflected in levels of the translated protein. Kisspeptin-immunoreactivity (IR) has been extensively examined using immunohistochemistry, enabling detection and localisation of kisspeptin perikaya in the arcuate nucleus (ARC) and anteroventral periventricular nucleus (AVPV). However, quantification of kisspeptin-IR remains challenging. We developed a specific rodent radioimmunoassay assay (RIA) capable of detecting and quantifying kisspeptin-IR in rodent tissues. The RIA uses kisspeptin-10 as a standard and radioactive tracer, combined with a commercially available antibody raised to the kisspeptin-10 fragment. Adult female wistar rat brain samples were sectioned at 300 µm and the ARC and AVPV punch micro-dissected. Brain punches were homogenised in extraction buffer and assayed with rodent kisspeptin-RIA. In accord with the pattern of kisspeptin mRNA expression, kisspeptin-IR was detected in both the ARC (47.1±6.2 fmol/punch, mean±SEM n = 15) and AVPV (7.6±1.3 fmol/punch, mean±SEM n = 15). Kisspeptin-IR was also detectable in rat placenta (1.26±0.15 fmol/mg). Reverse phase high pressure liquid chromatography analysis showed that hypothalamic kisspeptin-IR had the same elution profile as a synthetic rodent kisspeptin standard. A specific rodent kisspeptin-RIA will allow accurate quantification of kisspeptin peptide levels within specific tissues in rodent experimental models.     

Forecasting and Uncertainty Quantification Using a Hybrid of Mechanistic and Non-mechanistic Models for an Age-Structured Population Model

In this paper, we present a new method for the prediction and uncertainty quantification of data-driven multivariate systems. Traditionally, either mechanistic or non-mechanistic modeling methodologies have been used for prediction; however, it is uncommon for the two to be incorporated together. We compare the forecast accuracy of mechanistic modeling, using Bayesian inference, a non-mechanistic modeling approach based on state space reconstruction, and a novel hybrid methodology composed of the two for an age-structured population data set. The data come from cannibalistic flour beetles, in which it is observed that the adults preying on the eggs and pupae result in non-equilibrium population dynamics. Uncertainty quantification methods for the hybrid models are outlined and illustrated for these data. We perform an analysis of the results from Bayesian inference for the mechanistic model and hybrid models to suggest reasons why hybrid modeling methodology may enable more accurate forecasts of multivariate systems than traditional approaches.     

Comparative Metagenomic Analysis of Coral Microbial Communities Using a Reference-Independent Approach

By comparing the SEED and Pfam functional profiles of metagenomes of two Brazilian coral species with 29 datasets that are publicly available, we were able to identify some functions, such as protein secretion systems, that are overrepresented in the metagenomes of corals and may play a role in the establishment and maintenance of bacteria-coral associations. However, only a small percentage of the reads of these metagenomes could be annotated by these reference databases, which may lead to a strong bias in the comparative studies. For this reason, we have searched for identical sequences (99% of nucleotide identity) among these metagenomes in order to perform a reference-independent comparative analysis, and we were able to identify groups of microbial communities that may be under similar selective pressures. The identification of sequences shared among the metagenomes was found to be even better for the identification of groups of communities with similar niche requirements than the traditional analysis of functional profiles. This approach is not only helpful for the investigation of similarities between microbial communities with high proportion of unknown reads, but also enables an indirect overview of gene exchange between communities.     

An Emerging Approach for Parallel Quantification of Intracellular Protozoan Parasites and Host Cell Characterization Using TissueFAXS Cytometry

Characterization of host-pathogen interactions is a fundamental approach in microbiological and immunological oriented disciplines. It is commonly accepted that host cells start to change their phenotype after engulfing pathogens. Techniques such as real time PCR or ELISA were used to characterize the genes encoding proteins that are associated either with pathogen elimination or immune escape mechanisms. Most of such studies were performed in vitro using primary host cells or cell lines. Consequently, the data generated with such approaches reflect the global RNA expression or protein amount recovered from all cells in culture. This is justified when all host cells harbor an equal amount of pathogens under experimental conditions. However, the uptake of pathogens by phagocytic cells is not synchronized. Consequently, there are host cells incorporating different amounts of pathogens that might result in distinct pathogen-induced protein biosynthesis. Therefore, we established a technique able to detect and quantify the number of pathogens in the corresponding host cells using immunofluorescence-based high throughput analysis. Paired with multicolor staining of molecules of interest it is now possible to analyze the infection profile of host cell populations and the corresponding phenotype of the host cells as a result of parasite load.     

Assessment of Caspian Seal By-Catch in an Illegal Fishery Using an Interview-Based Approach

The Caspian seal (Pusa caspica) has declined by more than 90% since 1900 and is listed as endangered by IUCN. We made the first quantitative assessment of Caspian seal by-catch mortality in fisheries in the north Caspian Sea by conducting semi-structured interviews in fishing communities along the coasts of Russia (Kalmykia, Dagestan), Kazakhstan and Turkmenistan. We recorded a documented minimum by-catch of 1,215 seals in the survey sample, for the 2008–2009 fishing season, 93% of which occurred in illegal sturgeon fisheries. Due to the illegal nature of the fishery, accurately quantifying total fishing effort is problematic and the survey sample could reflect less than 10% of poaching activity in the north Caspian Sea. Therefore total annual by-catch may be significantly greater than the minimum documented by the survey. The presence of high by-catch rates was supported independently by evidence of net entanglement from seal carcasses, during a mass stranding on the Kazakh coast in May 2009, where 30 of 312 carcasses were entangled in large mesh sturgeon net remnants. The documented minimum by-catch may account for 5 to 19% of annual pup production. Sturgeon poaching therefore not only represents a serious threat to Caspian sturgeon populations, but may also be having broader impacts on the Caspian Sea ecosystem by contributing to a decline in one of the ecosystem’s key predators. This study demonstrates the utility of interview-based approaches in providing rapid assessments of by-catch in illegal small-scale fisheries, which are not amenable to study by other methods.     

Potency Analysis of Mesenchymal Stromal Cells Using a Combinatorial Assay Matrix Approach

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Bayesian Uncertainty Quantification for Bond Energies and Mobilities Using Path Integral Analysis

Dynamic single-molecule force spectroscopy is often used to distort bonds. The resulting responses, in the form of rupture forces, work applied, and trajectories of displacements, are used to reconstruct bond potentials. Such approaches often rely on simple parameterizations of one-dimensional bond potentials, assumptions on equilibrium starting states, and/or large amounts of trajectory data. Parametric approaches typically fail at inferring complicated bond potentials with multiple minima, while piecewise estimation may not guarantee smooth results with the appropriate behavior at large distances. Existing techniques, particularly those based on work theorems, also do not address spatial variations in the diffusivity that may arise from spatially inhomogeneous coupling to other degrees of freedom in the macromolecule. To address these challenges, we develop a comprehensive empirical Bayesian approach that incorporates data and regularization terms directly into a path integral. All experimental and statistical parameters in our method are estimated directly from the data. Upon testing our method on simulated data, our regularized approach requires less data and allows simultaneous inference of both complex bond potentials and diffusivity profiles. Crucially, we show that the accuracy of the reconstructed bond potential is sensitive to the spatially varying diffusivity and accurate reconstruction can be expected only when both are simultaneously inferred. Moreover, after providing a means for self-consistently choosing regularization parameters from data, we derive posterior probability distributions, allowing for uncertainty quantification.     

Verrucomicrobia Are Candidates for Polysaccharide-Degrading Bacterioplankton in an Arctic Fjord of Svalbard

In Arctic marine bacterial communities, members of the phylum Verrucomicrobia are consistently detected, although not typically abundant, in 16S rRNA gene clone libraries and pyrotag surveys of the marine water column and in sediments. In an Arctic fjord (Smeerenburgfjord) of Svalbard, members of the Verrucomicrobia, together with Flavobacteria and smaller proportions of Alpha- and Gammaproteobacteria, constituted the most frequently detected bacterioplankton community members in 16S rRNA gene-based clone library analyses of the water column. Parallel measurements in the water column of the activities of six endo-acting polysaccharide hydrolases showed that chondroitin sulfate, laminarin, and xylan hydrolysis accounted for most of the activity. Several Verrucomicrobia water column phylotypes were affiliated with previously sequenced, glycoside hydrolase-rich genomes of individual Verrucomicrobia cells that bound fluorescently labeled laminarin and xylan and therefore constituted candidates for laminarin and xylan hydrolysis. In sediments, the bacterial community was dominated by different lineages of Verrucomicrobia, Bacteroidetes, and Proteobacteria but also included members of multiple phylum-level lineages not observed in the water column. This community hydrolyzed laminarin, xylan, chondroitin sulfate, and three additional polysaccharide substrates at high rates. Comparisons with data from the same fjord in the previous summer showed that the bacterial community in Smeerenburgfjord changed in composition, most conspicuously in the changing detection frequency of Verrucomicrobia in the water column. Nonetheless, in both years the community hydrolyzed the same polysaccharide substrates.     

Quantification of Cyprinid Herpesvirus 3 in Environmental Water by Using an External Standard Virus

Cyprinid herpesvirus 3 (CyHV-3), a lethal DNA virus that spreads in natural lakes and rivers, infects common carp and koi. We established a quantification method for CyHV-3 that includes a viral concentration method and quantitative PCR combined with an external standard virus. Viral concentration methods were compared using the cation-coated filter and ultrafiltration methods. The recovery of virus-like particles was similar for the two methods (cation-coated filter method, 44% ± 19%, n = 3; ultrafiltration method, 50% ± 3%, n = 3); however, the former method was faster and more suitable for routine determinations. The recovery of seeded CyHV-3 based on the cation-coated filter method varied by more than 3 orders of magnitude among the water samples. The recovery yield of CyHV-3 was significantly correlated with that of the seeded λ phage, and the average ratio of λ to the CyHV-3 recovery yield was 1.4, indicating that λ is useful as an external standard virus for determining the recovery yield of CyHV-3. Therefore, to quantify CyHV-3 in environmental water, a known amount of λ was added as an external standard virus to each water sample. Using this method, CyHV-3 DNA was detected in 6 of the 10 (60%) types of environmental water tested; the highest concentration of CyHV-3 DNA was 2 × 10⁵ copies liter⁻¹. The lowest recovery limit of CyHV-3 DNA was 60 copies liter⁻¹. This method is practical for monitoring CyHV-3 abundance in environmental water.Cyprinid herpesvirus 3 (CyHV-3) is a lethal DNA virus that infects the common carp (Cyprinus carpio L.) and koi carp (C. carpio koi). The occurrence of the disease in the United Kingdom has been dated to 1996, following outbreaks in the United States, Israel, Europe, and South Asia (10), and has afflicted cultured ornamental and common carps, causing severe losses to fish breeders, retailers, and hobbyists (28). Therefore, the characterization and diagnosis of the disease have been the subject of intensive research (15). In recent years, the mortality of wild carp has been reported in natural freshwater environments (11, 18, 23). In Lake Biwa in Japan, 60 to 80% of the wild carp population (>100,000) died in 2004, presumably due to CyHV-3 infection (Shiga Prefectural Government, http://www.pref.shiga.jp/g/suisan-s/seika/files/seikah1711.pdf [in Japanese]) (18). The mass mortality of wild carp can directly and indirectly affect community composition and environmental ecosystems (18). Nevertheless, the occurrence of the disease and the means of transmission of CyHV-3 in the natural environment are still not well understood.CyHV-3 is present in several organs of infected fish, such as the intestines, kidneys (7), and gills (29). CyHV-3 is also detected in droppings (3); therefore, infected fish are suspected of releasing CyHV-3 into natural waters. Seasonal variation and the spatial distribution of CyHV-3 may be important for understanding the transmission routes and mechanisms by which CyHV-3 spreads. However, the lack of a reliable method for quantifying CyHV-3 in environmental water precludes our elucidation of how this disease spreads.In general, the concentration of a pathogen in environmental water is considerably lower than that found in host bodies. Therefore, a CyHV-3 concentration method is required to detect and quantify the virus in environmental water. Several methods have been developed for determining concentrations of viruses in water samples. Ultrafiltration can concentrate a pathogen from a large volume of water in <100 liters (27, 35). An alternative method involving the use of electronegative or electropositive microporous adsorbent filters has also been used to concentrate viruses from environmental water (1, 8). The mechanism of concentration in this method is based on electrostatic interactions. Haramoto et al. established a cation-coated filter method in which viruses that had been trapped were eluted with NaOH solution (pH 10.8) instead of the conventional solution, beef extract, which inhibits the PCR (12, 13). The concentrated viruses can then be used for PCR-mediated identification. Using this method, they succeeded in the qualitative detection of CyHV-3 DNA from river water samples (13).Viral recovery during concentration is influenced by soluble organic compounds (33, 34) and salts (31) in the water, which may vary in each sample. Therefore, quantification of the viral DNA from concentrated environmental water samples has been difficult. Because sediments contain many substances that influence DNA recovery, Mumy and Findlay developed a method for the routine determination of DNA extraction efficiency using an external DNA recovery standard, as follows: λ DNA was added to sediments, the total DNA was extracted, and the amount of target DNA recovered was determined by quantitative PCR (22).In this study, we established a method for quantifying CyHV-3 in environmental water using a viral concentration method and TaqMan PCR combined with an external standard virus. To choose a suitable viral concentration method, we compared the viral recovery yields between the ultrafiltration and cation-coated filter methods, and the procedure was modified to increase sensitivity. We then confirmed that the recovery yields of CyHV-3 and the external standard virus λ from different environmental waters throughout the procedure were positively correlated. Finally, we applied this method to environmental water samples taken from Lake Biwa and Takaragaike Pond in Japan at 3 years and 1 month, respectively, after an outbreak of the disease for the detection and quantification of CyHV-3.     

IDEAL-Q, an Automated Tool for Label-free Quantitation Analysis Using an Efficient Peptide Alignment Approach and Spectral Data Validation

In this study, we present a fully automated tool, called IDEAL-Q, for label-free quantitation analysis. It accepts raw data in the standard mzXML format as well as search results from major search engines, including Mascot, SEQUEST, and X!Tandem, as input data. To quantify as many identified peptides as possible, IDEAL-Q uses an efficient algorithm to predict the elution time of a peptide unidentified in a specific LC-MS/MS run but identified in other runs. Then, the predicted elution time is used to detect peak clusters of the assigned peptide. Detected peptide peaks are processed by statistical and computational methods and further validated by signal-to-noise ratio, charge state, and isotopic distribution criteria (SCI validation) to filter out noisy data. The performance of IDEAL-Q has been evaluated by several experiments. First, a serially diluted protein mixed with Escherichia coli lysate showed a high correlation with expected ratios and demonstrated good linearity (R² = 0.996). Second, in a biological replicate experiment on the THP-1 cell lysate, IDEAL-Q quantified 87% (1,672 peptides) of all identified peptides, surpassing the 45.7% (909 peptides) achieved by the conventional identity-based approach, which only quantifies peptides identified in all LC-MS/MS runs. Manual validation on all 11,940 peptide ions in six replicate LC-MS/MS runs revealed that 97.8% of the peptide ions were correctly aligned, and 93.3% were correctly validated by SCI. Thus, the mean of the protein ratio, 1.00 ± 0.05, demonstrates the high accuracy of IDEAL-Q without human intervention. Finally, IDEAL-Q was applied again to the biological replicate experiment but with an additional SDS-PAGE step to show its compatibility for label-free experiments with fractionation. For flexible workflow design, IDEAL-Q supports different fractionation strategies and various normalization schemes, including multiple spiked internal standards. User-friendly interfaces are provided to facilitate convenient inspection, validation, and modification of quantitation results. In summary, IDEAL-Q is an efficient, user-friendly, and robust quantitation tool. It is available for download.Quantitative analysis of protein expression promises to provide fundamental understanding of the biological changes or biomarker discoveries in clinical applications. In recent years, various stable isotope labeling techniques, e.g. ICAT (1), enzymatic labeling using ¹⁸O/¹⁶O (2, 3), stable isotope labeling by amino acids in cell culture (4), and isobaric tagging for relative and absolute quantitation (2, 5), coupled with LC-MS/MS have been widely used for large scale quantitative proteomics. However, several factors, such as the limited number of samples, the complexity of procedures in isotopic labeling experiments, and the high cost of reagents, limit the applicability of isotopic labeling techniques to high throughput analysis. Unlike the labeling approaches, the label-free quantitation approach quantifies protein expression across multiple LC-MS/MS analyses directly without using any labeling technique (7–9). Thus, it is particularly useful for analyzing clinical specimens in highly multiplexed quantitation (10, 11); theoretically, it can be used to compare any number of samples. Despite these significant advantages, data analysis in label-free experiments is an intractable problem because of the experimental procedures. First, although high reproducibility in LC is considered a critical prerequisite, variations, including the aging of separation columns, changes in sample buffers, and fluctuations in temperature, will cause a chromatographic shift in retention time for analytes in different LC-MS/MS runs and thus complicate the analysis. In addition, under the label-free approach, many technical replicate analyses across a large number of samples are often acquired; however, comparing a large number of data files further complicates data analysis and renders lower quantitation accuracy than that derived by labeling methods. Hence, an accurate, automated computation tool is required to effectively solve the problem of chromatographic shift, analyze a large amount of experimental data, and provide convenient user interfaces for manual validation of quantitation results.The rapid emergence of new label-free techniques for biomarker discovery has inspired the development of a number of bioinformatics tools in recent years. For example, Scaffold (Proteome Software) and Census (12) process PepXML search results to quantify relative protein expression based on spectral counting (13–15), which uses the number of MS/MS spectra assigned to a protein to determine the relative protein amount. Spectral counting has demonstrated a high correlation with protein abundance; however, to achieve good quantitation accuracy with the technique, high speed MS/MS data acquisition is required. Moreover, manipulations of the exclusion/inclusion strategy also affect the accuracy of spectral counting significantly. Because peptide level quantitation is also important for post-translational modification studies, the accuracy of spectral counting on peptide level quantitation deserves further study.Another type of quantitation analysis determines peptide abundance by MS¹ peak signals. According to some studies, MS¹ peak signals across different LC-MS/MS runs can be highly reproducible and correlate well with protein abundance in complex biological samples (7–9). Quantitation analysis methods based on MS¹ peak signals can be classified into three categories: identity-based, pattern-based, and hybrid-based methods (16). Identity-based methods (7–9) depend on the results of MS/MS sequencing to identify and detect peptide signals in MS¹ data. However, because the data acquisition speed of MS scanning is insufficient, a considerable number of low abundance peptides may not be selected for limited MS/MS sequencing. Only a few peptides can be repetitively identified in all LC-MS/MS runs and subsequently quantified; thus, only a small fraction of identified peptides are quantified, resulting in a small number of quantifiable peptides/proteins.In contrast to identity-based methods, pattern-based methods (17–23), including the publicly available MSight (20), MZmine (21, 22), and msInspect (23), tend to quantify all peptide peaks in MS¹ data to increase the number of quantifiable peptides. These methods first detect all peaks in each MS¹ data and then align the detected peaks across different LC-MS/MS runs. However, in pattern-based methods, efficient detection and alignment of the peaks between each pair of LC-MS/MS runs are a major challenge. To align the peaks, several methods based on dynamic programming or image pattern recognition have been proposed (24–26). The algorithms applied in these methods require intensive computation, and their computation time increases dramatically as the number of compared samples increases because all the LC-MS/MS runs must be processed. Therefore, pattern-based approaches are infeasible for processing a large number of samples. Furthermore, pattern recognition algorithms may fail on data containing noise or overlapping peptide signal (i.e. co-eluting peptides). The hybrid-based quantitation approach (16, 27–30) combines a pattern recognition algorithm with peptide identification results to align shifted peptides for quantitation. The pioneering accurate mass and time tag strategy (27) takes advantage of very sensitive, highly accurate mass measurement instruments with a wide dynamic range, e.g. FTICR-MS and TOF-MS, for quantitation analysis. PEPPeR (16) and SuperHirn (28) apply pattern recognition algorithms to align peaks and use the peptide identification results as landmarks to improve the alignment. However, because these methods still align all peaks in MS¹ data, they suffer the same computation time problem as pattern-based methods.To resolve the computation-intensive problem in the hybrid approach, we present a fully automated software system, called IDEAL-Q, for label-free quantitation including differential protein expression and protein modification analysis. Instead of using computation-intensive pattern recognition methods, IDEAL-Q uses a computation-efficient fragmental regression method for identity-based alignment of all confidently identified peptides in a local elution time domain. It then performs peptide cross-assignment by mapping predicted elution time profiles across multiple LC-MS experiments. To improve the quantitation accuracy, IDEAL-Q applies three validation criteria to the detected peptide peak clusters to filter out noisy signals, false peptide peak clusters, and co-eluting peaks. Because of the above key features, i.e. fragmental regression and stringent validation, IDEAL-Q can substantially increase the number of quantifiable proteins as well as the quantitation accuracy compared with other extracted ion chromatogram (XIC)¹ -based tools. Notably, to accommodate different designs, IDEAL-Q supports various built-in normalization procedures, including normalization based on multiple internal standards, to eliminate systematic biases. It also adapts to different fractionation strategies for in-depth proteomics profiling.We evaluated the performance of IDEAL-Q on three levels: 1) quantitation of a standard protein mixture, 2) large scale proteome quantitation using replicate cell lysate, and 3) proteome scale quantitative analysis of protein expression that incorporates an additional fractionation step. We demonstrated that IDEAL-Q can quantify up to 89% of identified proteins (703 proteins) in the replicate THP-1 cell lysate. Moreover, by manual validation of the entire 11,940 peptide ions corresponding to 1,990 identified peptides, 93% of peptide ions were accurately quantified. In another experiment on replicate data containing huge chromatographic shifts obtained from two independent LC-MS/MS instruments, IDEAL-Q demonstrated its robust quantitation and its ability to rectify such shifts. Finally, we applied IDEAL-Q to the THP-1 replicate experiment with an additional SDS-PAGE fractionation step. Equipped with user-friendly visualization interfaces and convenient data output for publication, IDEAL-Q represents a generic, robust, and comprehensive tool for label-free quantitative proteomics.