A review of 16 years of quality control parameters at a mass‐rearing facility producing Queensland fruit fly,Bactrocera tryoni

From 1996 to 2012, the mass‐rearing facility at Camden (NSW, Australia) has been producing Queensland fruit flies, Bactrocera tryoni (Froggatt) (Diptera: Tephritidae). During this time, the facility has regularly recorded fly quality parameters, creating a unique data set that provides an invaluable opportunity to evaluate the interrelationships among standard quality control (QC) parameters and test for redundant QC variables. Here, we conducted an exploratory data analysis to reveal relationships among the QC parameters. We found that pupal weight, adult lifespan, and longevity under nutritional stress (i.e., survival duration without food or water) had distinct monthly trends, suggesting that these QC parameters are sensitive to seasonal conditions. Furthermore, emergence percentage, flight ability, and adult lifespan were adversely affected by the dyeing/handling/irradiation process associated with sterile insect releases. Using a multivariate approach and controlling for monthly and yearly patterns, we showed that pupal weight and egg hatch are consistently negatively related and that percentage male and emergence rates are consistently negatively related. These results suggest that these correlation pairs measure similar quality information and hence one QC variable from each pair could be dropped. Flight ability was not strongly correlated with any of the QC variables, suggesting that this QC variable remains a useful QC metric. Finally, the longevity under nutritional stress QC appears to be fairly insensitive to QCs and we suggest that it should be replaced by the standard mortality under stress test.     

Guidelines and considerations for the use of system suitability and quality control samples in mass spectrometry assays applied in untargeted clinical metabolomic studies

Background

Quality assurance (QA) and quality control (QC) are two quality management processes that are integral to the success of metabolomics including their application for the acquisition of high quality data in any high-throughput analytical chemistry laboratory. QA defines all the planned and systematic activities implemented before samples are collected, to provide confidence that a subsequent analytical process will fulfil predetermined requirements for quality. QC can be defined as the operational techniques and activities used to measure and report these quality requirements after data acquisition.

Aim of review

This tutorial review will guide the reader through the use of system suitability and QC samples, why these samples should be applied and how the quality of data can be reported.

Key scientific concepts of review

System suitability samples are applied to assess the operation and lack of contamination of the analytical platform prior to sample analysis. Isotopically-labelled internal standards are applied to assess system stability for each sample analysed. Pooled QC samples are applied to condition the analytical platform, perform intra-study reproducibility measurements (QC) and to correct mathematically for systematic errors. Standard reference materials and long-term reference QC samples are applied for inter-study and inter-laboratory assessment of data.

     

Quality control of integral membrane proteins

Integral membrane proteins (IMPs) are essential components of the plasma and organellar membranes of the eukaryotic cell. Non-native IMPs, which can arise as a result of mutations, errors during biosynthesis or cellular stress, can disrupt these membranes and potentially lead to cell death. To protect against this outcome, the cell possesses quality control (QC) systems that detect and dispose of non-native IMPs from cellular membranes. Recent studies suggest that recognition of non-native IMPs by the QC machinery is correlated with the thermodynamic stability of these proteins. Consistent with this, small molecules known as chemical and pharmacological chaperones have been identified that stabilize non-native IMPs and enable them to evade QC. These findings have far-reaching implications for treating human diseases caused by defective IMPs.     

Assessing accuracy and precision for field and laboratory data: a perspective in ecosystem restoration

Unlike most laboratory studies, rigorous quality assurance/quality control (QA/QC) procedures may be lacking in ecosystem restoration (“ecorestoration”) projects, despite legislative mandates in the United States. This is due, in part, to ecorestoration specialists making the false assumption that some types of data (e.g. discrete variables such as species identification and abundance classes) are not subject to evaluations of data quality. Moreover, emergent behavior manifested by complex, adapting, and nonlinear organizations responsible for monitoring the success of ecorestoration projects tend to unconsciously minimize disorder, QA/QC being an activity perceived as creating disorder. We discuss similarities and differences in assessing precision and accuracy for field and laboratory data. Although the concepts for assessing precision and accuracy of ecorestoration field data are conceptually the same as laboratory data, the manner in which these data quality attributes are assessed is different. From a sample analysis perspective, a field crew is comparable to a laboratory instrument that requires regular “recalibration,” with results obtained by experts at the same plot treated as laboratory calibration standards. Unlike laboratory standards and reference materials, the “true” value for many field variables is commonly unknown. In the laboratory, specific QA/QC samples assess error for each aspect of the measurement process, whereas field revisits assess precision and accuracy of the entire data collection process following initial calibration. Rigorous QA/QC data in an ecorestoration project are essential for evaluating the success of a project, and they provide the only objective “legacy” of the dataset for potential legal challenges and future uses.     

High-throughput sample preparation procedures for the quantitation of a new bone integrin alpha(nu)beta(3) antagonist in human plasma and urine using liquid chromatography-tandem mass spectrometry

High throughput LC-MS/MS assays to quantitate a new alpha(nu)beta(3) bone integrin antagonist (I) in human plasma and urine have been developed using instruments programmed to automate sample preparation procedures. Packard liquid handling system-MultiPROBE II EX was programmed for preparing calibration standards in control plasma and urine, acidifying all standards, quality control (QC), and clinical samples with necessary dilutions, and adding the internal standard to the acidified samples. TOMTEC Quadra 96 was programmed to perform the solid phase extraction (SPE) process on a 3M 96-well mixed phase cation standard density (MPC-SD) plate to isolate the analytes from the sample matrix. The extract collected from both types of matrices was directly injected into reversed-phase LC-MS/MS system with a Turbo Ion Spray (TIS) interface in the positive ionization mode. The plasma and urine assays have the calibration range of 0.5-1500 and 2-6000 ng/mL, respectively. Validation of the automated and the manual plasma assays showed that application of MultiPROBE II to sample preparation gave comparable accuracy and precision. Overall, the automated approaches with minimum manual intervention enhanced the throughput of sample preparation.     

A two-stage, multilevel quality control system for serological assays in anthrax vaccine clinical trials

A two-stage, multilevel assay quality control (QC) system was designed and implemented for two high stringency QC anthrax serological assays; a quantitative anti-PA IgG enzyme-linked immunosorbent assay (ELISA) and an anthrax lethal toxin neutralization activity (TNA) assay. The QC system and the assays were applied for the congressionally mandated Centers for Disease Control and Prevention (CDC) Phase 4 human clinical trial of anthrax vaccine adsorbed (AVA, BioThrax). A total of 57,284 human serum samples were evaluated by anti-PA enzyme-linked immunosorbent assay (ELISA) and 11,685 samples by anthrax lethal toxin neutralization activity (TNA) assay. The QC system demonstrated overall sample acceptance rates of 86% for ELISA and 90% for the TNA assays respectively. Monitoring of multiple assay and test sample variables showed no significant long term trends or degradation in any of the critical assay reagents or reportable values for both assays. Assay quality control data establish the functionality of the quality control system and demonstrates the reliability of the serological data generated using these assays.     

Bioactivity-guided discovery of quality control markers in rhizomes of Curcuma wenyujin based on spectrum-effect relationship against human lung cancer cells

BackgroundDue to the diversity of the ingredients, the complexity of the mechanism of action, the uncertainty of the effective ingredients, coupled with the multiple species and multiple growing areas, the quality control (QC) of Traditional Chinese Medicines (TCMs) is challenging. Discovering and identifying effective compounds from the complex extracts of TCMs and then establishing a scientific QC method is the key to the holistic QC of TCMs.PurposeTo develop an anti-lung-cancer-guided spectrum-effect relationship approach for the discovery of QC markers of the rhizome of Curcuma wenyujin (WEZ) and establish a bioactive compounds-based holistic QC method.MethodsThe chemical profiling of the volatile oil (WVO) from 42 batches of WEZ collected from different growing areas was performed by GC-MS. The anti-lung cancer activity of different WVO samples was determined by CCK-8 assay against human lung cancer cells (A549). The apoptosis and cell cycle analysis under different concentrations of WVO were detected by flow cytometry. SIMCA-P software was used to perform multivariate statistical analysis on the chemical composition of different WVO samples and to find the different components. Active compounds were screened using a PLSR model of the spectrum-effect relationship. Bioactive compounds-based fingerprint and quantification of the leading bioactive compounds were developed by GC-MS and GC-FID, respectively.ResultsSeventy-eight compounds were detected in WVO and 54 were successfully identified. The multivariate statistical analysis uncovered that WVO components and the anti-A549 activity of WVO at the concentration of 60 nl/ml differ greatly according to the origin of the plant. The WVO at the concentration of 60 nl/ml (IC₅₀) increased A549 cells apoptosis significantly with late and early apoptosis of 15.61% and 7.80%, and the number of cells in the G2/M phase were also increased significantly under this concentration. The spectrum-effect relationship analysis revealed that 44 compounds were positively correlated with their activities, and the result was verified by A549 cell viability assay. Sixteen positively correlated compounds were further selected as QC markers according to their relative amount > 0.5% and anticancer activity. Finally, the 16 QC markers-based GC-MS fingerprint was established to holistically control the quality of WEZ, and a GC-FID method was developed for the quantification of leading bioactive compounds, β-elemene and β-caryophyllene.ConclusionBased on an anti-lung-cancer-guided spectrum-effect relationship approach, the bioactive compounds-based holistic QC method was successfully developed for WEZ, which could provide a valuable reference for the QC of TCMs.     

Liquid chromatography-tandem mass spectrometric quantitative determination of the HIV protease inhibitor atazanavir (BMS-232632) in human peripheral blood mononuclear cells (PBMC): practical approaches to PBMC preparation and PBMC assay design for high-throughput analysis

A selective, accurate, and reproducible LC/MS/MS assay was developed and validated for the determination of the HIV protease inhibitor atazanavir (BMS-232632) in human peripheral blood mononuclear cells (PBMC) samples. In addition to the details of the validated LC/MS/MS method, a practical procedure is described in great detail for the preparation of large supplies of control (blank) PBMC from units of blood (each unit of blood is about 500 ml) for making the calibration standards and quality control (QC) samples. The PBMC assay design, intended for high-throughput sample analysis, is also described in some detail in regards to the composition and concentration expressions of the calibration standards and QC samples, the lysing procedure of the PBMC samples, and the final analysis/quantitation procedure. The method involved automated solid-phase extraction (SPE) of atazanavir and a stable isotope analog internal standard (I.S.) using 3M Empore C2-SD 96-well plates. A portion of the reconstituted sample residue was injected onto a YMC Basic analytical column which was connected to a triple quad mass spectrometer for analyte determination by positive-ion electrospray in the selected reaction monitoring (SRM) mode. The standard curve, which ranged from 5 to 2500 fmol per one million cells (fmol/10(6) cells), was fitted to a quadratic regression model weighted by 1/concentration. The lower limit of quantitation (LLOQ) was 5 fmol/10(6) cells. The inter- and intra-run coefficients of variation (CV) for the assay were <9% and the accuracy was 94-104%. Atazanavir was stable in PBMC for at least 24h at room temperature and for at least 129 days at -15 degrees C.     

Optimal sampling strategy for estimation of spatial genetic structure in tree populations

Fine-scale spatial genetic structure (SGS) in natural tree populations is largely a result of restricted pollen and seed dispersal. Understanding the link between limitations to dispersal in gene vectors and SGS is of key interest to biologists and the availability of highly variable molecular markers has facilitated fine-scale analysis of populations. However, estimation of SGS may depend strongly on the type of genetic marker and sampling strategy (of both loci and individuals). To explore sampling limits, we created a model population with simulated distributions of dominant and codominant alleles, resulting from natural regeneration with restricted gene flow. SGS estimates from subsamples (simulating collection and analysis with amplified fragment length polymorphism (AFLP) and microsatellite markers) were correlated with the 'real' estimate (from the full model population). For both marker types, sampling ranges were evident, with lower limits below which estimation was poorly correlated and upper limits above which sampling became inefficient. Lower limits (correlation of 0.9) were 100 individuals, 10 loci for microsatellites and 150 individuals, 100 loci for AFLPs. Upper limits were 200 individuals, five loci for microsatellites and 200 individuals, 100 loci for AFLPs. The limits indicated by simulation were compared with data sets from real species. Instances where sampling effort had been either insufficient or inefficient were identified. The model results should form practical boundaries for studies aiming to detect SGS. However, greater sample sizes will be required in cases where SGS is weaker than for our simulated population, for example, in species with effective pollen/seed dispersal mechanisms.     

Simultaneous supercritical fluid extraction and chemical derivatization for the gas chromatographic–isotope dilution mass spectrometric determination of amphetamine and methamphetamine in urine

An in-situ supercritical fluid extraction (SFE) and chemical derivatization (ChD) procedure followed by gas chromatography–isotope dilution mass spectrometry (GC–MS) for the determination of amphetamines in urine is described and evaluated. While using celite as the SFE wet-support, the one-pot sample pretreatment procedure also employs ammonium water to alkalize the urine matrix that contains protonated amphetamine (AP) and methamphetamine (MA). The mean recoveries achieved by simultaneous SFE–ChD, i.e., 95% (RSD=3.8%) for AP and 89% (RSD=4.0%) for MA, are significantly better than the corresponding overall recoveries obtained upon stepwise SFE–ChD, suggesting the unreacted trifluoroacetic anhydride (TFA) in the former procedure has strengthened the extracting power of CO₂ fluid as has been evidenced by a control test. As to GC–MS analysis, the optimal qualitative ions and quantitative ions of the respective analytes were determined via a rigorous evaluation process. Thus, the regression calibration curves for AP and MA in urine are linear within 100∼50 000 ng/ml, with correlation coefficients typically exceeding 0.999. The limits of detection determined by two methods for AP and MA vary from 19 to 50 ng/ml, and limits of quantitation from 21 to 100 ng/ml. Precisions calculated for the triplicate analyses of AP and MA in a 500-ng/ml spiked control, two real-case samples and two quasi real-case samples, respectively, using regression calibration are typically below 10%. The method is simple and reliable. It may serve as an alternative to the existing confirmatory protocol for forensic urine drug testing.     

Analysis of microsomal metabolic stability using high-flow-rate extraction coupled to capillary liquid chromatography-mass spectrometry

A method is described for on-line high-speed extraction of microsomal samples and analysis by capillary liquid chromatography-mass spectrometry (LC-MS) for the determination of metabolic stability in connection with the development of positron emission tomography (PET) tracers. The method allowed direct injections of large sample volumes at a fast extraction rate, providing a gain in both sensitivity and sample preparation time. The calibration curve of the test compound flumazenil (Ro 15-1788) was linear in the concentration range of 1-150 nM, with a correlation coefficient exceeding 0.999. The accuracy of the method ranged from 98 to 101%. A high precision was obtained, with mean intra-assay and inter-assay relative standard deviations of at most 1.4 and 1.5%, respectively, for quality control (QC) samples. The extraction efficiency was determined to be 99.4%, the total recovery 96% and the carryover to 相似文献   

Simultaneous quantitation of 7-methyl- and O6-methylguanine adducts in DNA by liquid chromatography-positive electrospray tandem mass spectrometry

A methodology has been developed and validated for the simultaneous quantitation of O6-methyl- and 7-methylguanine in DNA isolated from in vitro exposure to the model alkylating agents: N-methyl-N-nitrosourea (MNU) and methyl methane sulfonate (MMS). After exposure, DNA was isolated and directly hydrolyzed under acid conditions to hydrolytes containing DNA bases (modified and unmodified). The hydrolytes were used for direct O6- and 7-methylguanine quantitation using a rapid and selective liquid chromatography-electrospray tandem mass spectrometry (LC/ESI-MS/MS). The lower limits of quantitation for O6-methyl- and 7-methylguanine were 75.8 and 151.5 fmol, respectively. Linearity of the calibration curve was greater than 0.999 from 75.8 to 151,600.0 fmol for O6-methylguanine and 0.999 from 151.5 to 303,200.0 fmol for 7-methylguanine. The intra-day assay precision relative standard deviation (R.S.D.) values for O6-methylguanine for quality control (QC) samples were < or =9.2% with accuracy values ranging from 90.8 to 118%, and for 7-methylguanine the R.S.D. values for QC samples were < or =11%, with accuracy values ranging from 92.9 to 119%. The inter-day assay precision (R.S.D.) values for O6-methylguanine QC samples were < or =7.9% with accuracy values ranging from 94.5 to 116%, and for 7-methylguanine QC samples were < or =7.1% with accuracy values ranging from 95.2 to 110.2%. This method was used for simultaneous determination of the levels of 7-methyl- and O6-methylguanine in DNA acidic hydrolytes present in a series of incubations from salmon testis DNA treated with either MNU or MMS.     

Evaluating the influence of quality control decisions and software algorithms on SNP calling for the affymetrix 6.0 SNP array platform

Objective: Our goal was to evaluate the influence of quality control (QC) decisions using two genotype calling algorithms, CRLMM and Birdseed, designed for the Affymetrix SNP Array 6.0. Methods: Various QC options were tried using the two algorithms and comparisons were made on subject and call rate and on association results using two data sets. Results: For Birdseed, we recommend using the contrast QC instead of QC call rate for sample QC. For CRLMM, we recommend using the signal-to-noise rate ≥4 for sample QC and a posterior probability of 90% for genotype accuracy. For both algorithms, we recommend calling the genotype separately for each plate, and dropping SNPs with a lower call rate (<95%) before evaluating samples with lower call rates. To investigate whether the genotype calls from the two algorithms impacted the genome-wide association results, we performed association analysis using data from the GENOA cohort; we observed that the number of significant SNPs were similar using either CRLMM or Birdseed. Conclusions: Using our suggested workflow both algorithms performed similarly; however, fewer samples were removed and CRLMM took half the time to run our 854 study samples (4.2 h) compared to Birdseed (8.4 h).     

Prevention,diagnosis and treatment of high‐throughput sequencing data pathologies

High‐throughput sequencing (HTS) technologies generate millions of sequence reads from DNA/RNA molecules rapidly and cost‐effectively, enabling single investigator laboratories to address a variety of ‘omics’ questions in nonmodel organisms, fundamentally changing the way genomic approaches are used to advance biological research. One major challenge posed by HTS is the complexity and difficulty of data quality control (QC). While QC issues associated with sample isolation, library preparation and sequencing are well known and protocols for their handling are widely available, the QC of the actual sequence reads generated by HTS is often overlooked. HTS‐generated sequence reads can contain various errors, biases and artefacts whose identification and amelioration can greatly impact subsequent data analysis. However, a systematic survey on QC procedures for HTS data is still lacking. In this review, we begin by presenting standard ‘health check‐up’ QC procedures recommended for HTS data sets and establishing what ‘healthy’ HTS data look like. We next proceed by classifying errors, biases and artefacts present in HTS data into three major types of ‘pathologies’, discussing their causes and symptoms and illustrating with examples their diagnosis and impact on downstream analyses. We conclude this review by offering examples of successful ‘treatment’ protocols and recommendations on standard practices and treatment options. Notwithstanding the speed with which HTS technologies – and consequently their pathologies – change, we argue that careful QC of HTS data is an important – yet often neglected – aspect of their application in molecular ecology, and lay the groundwork for developing a HTS data QC ‘best practices’ guide.     

Announcement—guidance document for acquiring reliable data in ecological restoration projects

The Laurentian Great Lakes are undergoing intensive ecological restoration in Canada and the United States. In the United States, an interagency committee was formed to facilitate implementation of quality practices for federally funded restoration projects in the Great Lakes basin. The Committee's responsibilities include developing a guidance document that will provide a common approach to the application of quality assurance and quality control (QA/QC) practices for restoration projects. The document will serve as a “how‐to” guide for ensuring data quality during each aspect of ecological restoration projects. In addition, the document will provide suggestions on linking QA/QC data with the routine project data and hints on creating detailed supporting documentation. Finally, the document will advocate integrating all components of the project, including QA/QC applications, into an overarching decision‐support framework. The guidance document is expected to be released by the U.S. EPA Great Lakes National Program Office in 2017.     

Simultaneous determination of flupirtine and its major active metabolite in human plasma by liquid chromatography–tandem mass spectrometry

A rapid, selective and sensitive HPLC–tandem mass spectrometry method was developed and validated for simultaneous determination of flupirtine and its active metabolite D-13223 in human plasma. The analytes and internal standard diphenhydramine were extracted from plasma samples by liquid–liquid extraction, and chromatographed on a C₁₈ column. The mobile phase consisted of acetonitrile–water–formic acid (60:40:1, v/v/v), at a flow rate of 0.5 ml/min. Detection was performed on a triple quadrupole tandem mass spectrometer by selected reaction monitoring (SRM) mode via atmospheric pressure chemical ionization (APCI). The method has a limit of quantitation of 10 ng/ml for flupirtine and 2 ng/ml for D-13223, using 0.5-ml plasma sample. The linear calibration curves were obtained in the concentration range of 10.0–1500.0 ng/ml for flupirtine and 2.0–300.0 ng/ml for D-13223. The intra- and inter-run precision (RSD), calculated from quality control (QC) samples was less than 7.2% for flupirtine and D-13223. The accuracy as determined from QC samples was less than 5% for the analytes. The overall extraction recoveries of flupirtine and D-13223 were determined to be about 66% and 78% on average, respectively. The method was applied for the evaluation of the pharmacokinetics of flupirtine and active metabolite D-13223 in volunteers following peroral administration.     

Reconstructing paleoecology and paleoenvironmental variables using factor analysis and regression: some limitations

We test the success of Principal Components, Factor and Regression Analysis at recovering environmental signals using numerical experiments in which we control species environmental responses, the environmental conditions and the sampling scheme used for calibration. We use two general conditions, one in which sampling of a continental margin for benthic foraminiferal assemblages is done in a standard grid and the driving environmental variables are correlated to one another, and the other where sampling is done so that the environmental variables are uncorrelated. The first condition mimics many studies in the literature. We find that where the controlling environmental variables are correlated, Principal Components/Factor Analysis yield factors that reflect the common variance (correlation) of those variables. Since this common variance is largely a product of the sampling scheme, the factors extracted do not reliably present true species ecologic behavior. This behavior cannot be accurately diagnosed and faulty interpretations may lead to substantial error when using factor coefficients to reconstruct conditions in the past. When the sampling scheme is constructed so that the controlling environmental variables for the calibration data set are uncorrelated the factor patterns will reflect these variables more accurately. Species responses can be more successfully interpreted from the Principal Components/Factor Analysis structure matrices. Additionally, regression analysis can successfully extract the independent environmental signals from the biotic data set. However, matrix closure is a confounding effect in all our numerical results as it distorts species' abundances and spatial distribution in the calibration data set. Our results show clearly that a knowledge of the controlling environmental variables, and the correlations among these variables over a study area, is essential for the successful application of multivariate techniques for paleoenvironmental reconstruction.     

Developing a robust ultrafiltration-LC-MS/MS method for quantitative analysis of unbound vadimezan (ASA404) in human plasma

Ultrafiltration of human plasma in combination with LC-MS/MS has been increasingly used in the quantitative analysis of the free fraction of drug candidates for PK/efficacy assessment. In addition to controlling the pre-incubation and centrifugation temperatures, some important factors that must be investigated and addressed include: (1) possible nonspecific binding, (2) possible impact of freeze/thaw cycles of plasma samples and extended storage of plasma samples at room temperature on the analyte recovery prior to ultrafiltration, and (3) identification of the appropriate assay dynamic range to avoid unnecessary dilutions. These factors were explored in the development and validation of a robust LC-MS/MS assay for the quantitative analysis of unbound vadimezan (ASA404) in human plasma. First, to mimic human physiological conditions, all plasma samples were incubated at ~37°C for a minimum of 30 min after thawing and prior to centrifugation to obtain the ultrafiltrate. Second, by passing the calibration standards and QC samples in plasma ultrafiltrate through the ultrafiltration membrane, the observed non-specific binding of the analyte due to the membrane was corrected. Third, the effects of multiple freeze/thaw cycles and/or storage at room temperature for various periods (4, 8, 16 and 24h) were evaluated to determine the impact on analyte concentrations in the ultrafiltrate from the plasma QC samples. Fourth, the appropriate dynamic range was established to accommodate the expected incurred sample free analyte concentrations. The validated assay has a dynamic range of 30.0-30,000 ng/ml for ASA404 in human plasma ultrafiltrate using a sample volume of 30 μl. Quality control pools containing the analyte were prepared at concentrations of 30.0-22,500 ng/ml to cover the assay calibration range. The intra-assay and inter-assay precision and accuracy were ≤ 15% (CV) and within ± 15% (bias) of the nominal values, respectively, for all measured QC concentrations, including the LLOQ. Freeze/thaw for up to three cycles of the plasma samples and/or the extended human plasma sample exposure to room temperature for up to 24h were confirmed to have no impact on the assay results for the free analyte. The validated method was successfully implemented to support clinical studies for the compound.     

Standardization of a broth microdilution susceptibility testing method to determine minimum inhibitory concentrations of aquatic bacteria

A multiple laboratory study was conducted in accordance with the standards established by the Clinical and Laboratory Standards Institute (CLSI), formerly the National Committee for Clinical Laboratory Standards (NCCLS), for the development of quality control (QC) ranges using dilution antimicrobial susceptibility testing methods for bacterial isolates from aquatic animal species. QC ranges were established for Escherichia coli ATCC 25922 and Aeromonas salmonicida subsp. salmonicida ATCC 33658 when testing at 22, 28 and 35 degrees C (E. coli only) for 10 different antimicrobial agents (ampicillin, enrofloxacin, erythromycin, florfenicol, flumequine, gentamicin, ormetoprim/sulfadimethoxine, oxolinic acid, oxytetracycline and trimethoprim/sulfamethoxazole). Minimum inhibitory concentration (MIC) QC ranges were determined using dry- and frozen-form 96-well plates and cation-adjusted Mueller-Hinton broth. These QC ranges were accepted by the CLSI/NCCLS Subcommittee on Veterinary Antimicrobial Susceptibility Testing in January 2004. This broth microdilution testing method represents the first standardized method for determining MICs of bacterial isolates whose preferred growth temperatures are below 35 degrees C. Methods and QC ranges defined in this study will enable aquatic animal disease researchers to reliably compare quantitative susceptibility testing data between laboratories, and will be used to ensure both precision and inter-laboratory harmonization.     

Meta-QC-Chain: Comprehensive and Fast Quality Control Method for Metagenomic Data

Next-generation sequencing(NGS) technology has revolutionized and significantly impacted metagenomic research.However,the NGS data usually contains sequencing artifacts such as low-quality reads and contaminating reads,which will significantly compromise downstream analysis.Many quality control(QC) tools have been proposed,however,few of them have been verified to be suitable or efficient for metagenomic data,which are composed of multiple genomes and are more complex than other kinds of NGS data.Here we present a metagenomic data QC method named Meta-QC-Chain.Meta-QC-Chain combines multiple QC functions:technical tests describe input data status and identify potential errors,quality trimming filters poor sequencing-quality bases and reads,and contamination screening identifies higher eukaryotic species,which are considered as contamination for metagenomic data.Most computing processes are optimized based on parallel programming.Testing on an 8-GB real dataset showed that Meta-QC-Chain trimmed low sequencing-quality reads and contaminating reads,and the whole quality control procedure was completed within 20 min.Therefore,Meta-QC-Chain provides a comprehensive,useful and high-performance QC tool for metagenomic data.Meta-QC-Chain is publicly available for free at:http://computationalbioenergy.org/meta-qc-chain.html.