A flow cytometric assay to detect viability and persistence of subsp. serotypes in nuclease-free water at 4 and 25°C.

spp. is one of the most isolated microorganisms reported to be responsible for human foodborne diseases and death. Water constitutes a major reservoir where the spp.

Specific Detection and Enumeration of Complex by Flow Cytometry Using a Fluorescence-Labeled Oligonucleotide Probe.

complex (BCC) contamination has resulted in recalls of non-sterile pharmaceutical products. The fast, sensitive, and specific detection of BCC is critical for ensuring the quality and safety of pharmaceutical products. In this study, a rapid flow cytometry-based detection method was developed using a fluorescence-labeled oligonucleotide probe that specifically binds a KefB/KefC membrane protein sequence within BCC.

Draft Genome Sequence of Ralstonia pickettii Strain NCTR106, Isolated from Milk Carton Paperboard.

Ralstonia pickettii is an emerging global opportunistic pathogen. Here, we report the 5.3-Mbp draft genome sequence of NCTR106, isolated from milk carton paperboard obtained from a commercial paper mill.

A comparison of culture-based, real-time PCR, droplet digital PCR and flow cytometric methods for the detection of Burkholderia cepacia complex in nuclease-free water and antiseptics.

The presence of Burkholderia cepacia complex (BCC) strains has resulted in recalls of pharmaceutical products, since these opportunistic pathogens can cause serious infections. Rapid and sensitive diagnostic methods to detect BCC are crucial to determine contamination levels. We evaluated bacterial cultures, real-time PCR (qPCR), droplet digital PCR (ddPCR), and flow cytometry to detect BCC in nuclease-free water, in chlorhexidine gluconate (CHX) and benzalkonium chloride (BZK) solutions.

Rapid Flow Cytometry Detection of a Single Viable O157:H7 Cell in Raw Spinach Using a Simplified Sample Preparation Technique.

Very low cell count detection of O157:H7 in foods is critical, since an infective dose for this pathogen may be only 10 cells, and fewer still for vulnerable populations. A flow cytometer is able to detect and count individual cells of a target bacterium, in this case O157:H7. The challenge is to find the single cell in a complex matrix like raw spinach.

Flow-Cytometry-Based Method to Detect Escherichia coli and Shigella Spp. Using 16S rRNA-Based Probe.

Detection of microbial contamination in foods before they go on to the market can help prevent the occurrence of foodborne illness outbreaks. Current methods for the detection of Escherichia coli are limited by time-consuming procedures, which include multiple culture incubation steps, and require several days to get results. This unit describes the development of an improved rapid flow-cytometry-based detection method that has greater sensitivity and specificity.

3D-SDAR modeling of hERG potassium channel affinity: A case study in model design and toxicophore identification.

A dataset of 237 human Ether-à-go-go Related Gene (hERG) potassium channel inhibitors (180 of which were used for model building and validation, whereas 57 constituted the "true" external prediction set) collected from 22 literature sources was modeled by 3D-SDAR. To produce reliable and reproducible classification models for hERG blocking, the initial set of 180 chemicals was split into two subsets: a balanced modeling set consisting of 118 compounds and an unbalanced validation set comprised of 62 compounds. A PLS bagging-like algorithm written in Matlab was used to process the data and assign each compound to one of the two (hERG+ or hERG-) activity classes.

Alignment-independent technique for 3D QSAR analysis.

Molecular biochemistry is controlled by 3D phenomena but structure-activity models based on 3D descriptors are infrequently used for large data sets because of the computational overhead for determining molecular conformations. A diverse dataset of 146 androgen receptor binders was used to investigate how different methods for defining molecular conformations affect the performance of 3D-quantitative spectral data activity relationship models. Molecular conformations tested: (1) global minimum of molecules' potential energy surface; (2) alignment-to-templates using equal electronic and steric force field contributions; (3) alignment using contributions "Best-for-Each" template; (4) non-energy optimized, non-aligned (2D > 3D).

Development of a Flow Cytometry-Based Method for Rapid Detection of Escherichia coli and Shigella Spp. Using an Oligonucleotide Probe.

Standard methods to detect Escherichia coli contamination in food use the polymerase chain reaction (PCR) and agar culture plates. These methods require multiple incubation steps and take a long time to results. An improved rapid flow-cytometry based detection method was developed, using a fluorescence-labeled oligonucleotide probe specifically binding a16S rRNA sequence.

Level 2 validation of a flow cytometric method for detection of Escherichia coli O157:H7 in raw spinach.

The Bacteriological Analytical Manual (BAM) method currently used by the United States Food and Drug Administration (FDA) to detect Escherichia coli O157:H7 in spinach was systematically compared to a new flow cytometry based method. This Food and Drug Administration (FDA) level 2 external laboratory validation study was designed to determine the latter method's sensitivity and speed for analysis of this pathogen in raw spinach. Detection of target cell inoculations with a low cell count is critical, since enterohemorrhagic strains of E.

Computational identification of a phospholipidosis toxicophore using (13)C and (15)N NMR-distance based fingerprints.

Modified 3D-SDAR fingerprints combining (13)C and (15)N NMR chemical shifts augmented with inter-atomic distances were used to model the potential of chemicals to induce phospholipidosis (PLD). A curated dataset of 328 compounds (some of which were cationic amphiphilic drugs) was used to generate 3D-QSDAR models based on tessellations of the 3D-SDAR space with grids of different density. Composite PLS models averaging the aggregated predictions from 100 fully randomized individual models were generated.

An integrated flow cytometry-based system for real-time, high sensitivity bacterial detection and identification.

Foodborne illnesses occur in both industrialized and developing countries, and may be increasing due to rapidly evolving food production practices. Yet some primary tools used to assess food safety are decades, if not centuries, old. To improve the time to result for food safety assessment a sensitive flow cytometer based system to detect microbial contamination was developed.

Partial least square and k-nearest neighbor algorithms for improved 3D quantitative spectral data-activity relationship consensus modeling of acute toxicity.

A diverse set of 154 chemicals that included US Food and Drug Administration-regulated compounds tested for their aquatic toxicity in Daphnia magna were modeled by a 3-dimensional quantitative spectral data-activity relationship (3D-QSDAR). Two distinct algorithms, partial least squares (PLS) and Tanimoto similarity-based k-nearest neighbors (KNN), were used to process bin occupancy descriptor matrices obtained after tessellation of the 3D-QSDAR space into regularly sized bins. The performance of models utilizing bins ranging in size from 2 ppm × 2 ppm × 0.

Complementary PLS and KNN algorithms for improved 3D-QSDAR consensus modeling of AhR binding.

Multiple validation techniques (Y-scrambling, complete training/test set randomization, determination of the dependence of R2test on the number of randomization cycles, etc.) aimed to improve the reliability of the modeling process were utilized and their effect on the statistical parameters of the models was evaluated. A consensus partial least squares (PLS)-similarity based k-nearest neighbors (KNN) model utilizing 3D-SDAR (three dimensional spectral data-activity relationship) fingerprint descriptors for prediction of the log(1/EC50) values of a dataset of 94 aryl hydrocarbon receptor binders was developed.

Photobleaching with phloxine B sensitizer to reduce food matrix interference for detection of Escherichia coli serotype O157:H7 in fresh spinach by flow cytometry.

A flow cytometric method (RAPID-B™) with detection sensitivity of one viable cell of Escherichia coli serotype O157:H7 in fresh spinach (Spinacia oleracea) was developed and evaluated. The major impediment to achieving this performance was mistaking autofluorescing spinach particles for tagged target cells. Following a 5 h non-selective enrichment, artificially inoculated samples were photobleached, using phloxine B as a photosensitizer.

¹³C NMR-distance matrix descriptors: optimal abstract 3D space granularity for predicting estrogen binding.

An improved three-dimensional quantitative spectral data-activity relationship (3D-QSDAR) methodology was used to build and validate models relating the activity of 130 estrogen receptor binders to specific structural features. In 3D-QSDAR, each compound is represented by a unique fingerprint constructed from (13)C chemical shift pairs and associated interatomic distances. Grids of different granularity can be used to partition the abstract fingerprint space into congruent "bins" for which the optimal size was previously unexplored.

Modeling chemical interaction profiles: II. Molecular docking, spectral data-activity relationship, and structure-activity relationship models for potent and weak inhibitors of cytochrome P450 CYP3A4 isozyme.

Polypharmacy increasingly has become a topic of public health concern, particularly as the U.S. population ages.

Modeling chemical interaction profiles: I. Spectral data-activity relationship and structure-activity relationship models for inhibitors and non-inhibitors of cytochrome P450 CYP3A4 and CYP2D6 isozymes.

An interagency collaboration was established to model chemical interactions that may cause adverse health effects when an exposure to a mixture of chemicals occurs. Many of these chemicals--drugs, pesticides, and environmental pollutants--interact at the level of metabolic biotransformations mediated by cytochrome P450 (CYP) enzymes. In the present work, spectral data-activity relationship (SDAR) and structure-activity relationship (SAR) approaches were used to develop machine-learning classifiers of inhibitors and non-inhibitors of the CYP3A4 and CYP2D6 isozymes.

Reduction of food matrix interference by a combination of sample preparation and multi-dimensional gating techniques to facilitate rapid, high sensitivity analysis for Escherichia coli serotype O157 by flow cytometry.

Escherichia coli serotype O157 strains, which may be found in foods, often produce enterohemorrhagic toxins. The research goal was to facilitate rapid, sensitive detection in foods of E. coli serotype O157 by flow cytometry.

Improving proton MR spectroscopy of brain tissue for noninvasive diagnostics.

Purpose: To examine preprocessing methods affecting the potential use of Magnetic Resonance Spectroscopy (MRS) as a noninvasive modality for detection and characterization of brain lesions and for directing therapy progress.

Materials And Methods: Two reference point re-calibration with linear interpolation (to compensate for magnetic field nonhomogeneity), weighting of spectra (to emphasize consistent peaks and depress chemical noise), and modeling based on chemical shift locations of 97 biomarkers were investigated. Results for 139 categorized scans were assessed by comparing Leave-One-Out (LOO) cross-validation and external validation.

Modeling and assaying dioxin-like biological effects for both dioxin-like and certain non-dioxin-like compounds.

13C NMR data have been correlated to Toxic Equivalency Factors (TEFs) of the 29 PCDDs, PCDFs, or PCBs for which non-zero TEFs have been defined. Such correlations are called quantitative spectrometric data-activity relationship (QSDAR) models. An improved QSDAR model predicted TEFs of 0.

Pyrolysis mass spectrometry for distinguishing potential hoax materials from bioterror agents.

Pyrolysis mass spectrometry (PyMS) was investigated as a rapid tool to distinguish potential bioterror hoax materials from samples containing pathogenic bacteria. A pyrolysis time-of-flight (TOF) mass spectrometer equipped with an alternative ionization technique, metastable atom bombardment (MAB), was used to produce sample spectra. These spectra were analyzed by principal component and discriminant analysis for pattern recognition.

Improved cell typing by charge-state deconvolution of matrix-assisted laser desorption/ionization mass spectra.

Robust, specific, and rapid identification of toxic strains of bacteria and viruses, to guide the mitigation of their adverse health effects and optimum implementation of other response actions, remains a major analytical challenge. This need has driven the development of methods for classification of microorganisms using mass spectrometry, particularly matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS), that allows high-throughput analyses with minimum sample preparation. We describe a novel approach to cell typing based on pattern recognition of MALDI mass spectra, which involves charge-state deconvolution in conjunction with a new correlation analysis procedure.

Rapid phenotypic characterization of Salmonella enterica strains by pyrolysis metastable atom bombardment mass spectrometry with multivariate statistical and artificial neural network pattern recognition.

Pyrolysis mass spectrometry was investigated for rapid characterization of bacteria. Spectra of Salmonella were compared to their serovars, pulsed-field gel electrophoresis (PFGE) patterns, antibiotic resistance profiles, and MIC values. Pyrolysis mass spectra generated via metastable atom bombardment were analyzed by multivariate principal component-discriminant analysis and artificial neural networks (ANNs).