Valery Patsekin

Light-scattering sensor for real-time identification of Vibrio parahaemolyticus, Vibrio vulnificus and Vibrio cholerae colonies on solid agar plate.

The three most common pathogenic species of Vibrio, Vibrio cholerae, Vibrio parahaemolyticus and Vibrio vulnificus, are of major concerns due to increased incidence of water‐ and seafood‐related outbreaks and illness worldwide. Current methods are lengthy and require biochemical and molecular confirmation. A novel label‐free forward light‐scattering sensor was developed to detect and identify colonies of these three pathogens in real time in the presence of other vibrios in food or water samples. Vibrio colonies grown on agar plates were illuminated by a 635 nm laser beam and scatter‐image signatures were acquired using a CCD (charge‐coupled device) camera in an automated BARDOT (BActerial Rapid Detection using Optical light‐scattering Technology) system. Although a limited number of Vibrio species was tested, each produced a unique light‐scattering signature that is consistent from colony to colony. Subsequently a pattern recognition system analysing the collected light‐scatter information provided classification in 1−2 min with an accuracy of 99%. The light‐scattering signatures were unaffected by subjecting the bacteria to physiological stressors: osmotic imbalance, acid, heat and recovery from a viable but non‐culturable state. Furthermore, employing a standard sample enrichment in alkaline peptone water for 6 h followed by plating on selective thiosulphate citrate bile salts sucrose agar at 30°C for ∼ 12 h, the light‐scattering sensor successfully detected V. cholerae, V. parahaemolyticus and V. vulnificus present in oyster or water samples in 18 h even in the presence of other vibrios or other bacteria, indicating the suitability of the sensor as a powerful screening tool for pathogens on agar plates.

Hyperspectral cytometry at the single-cell level using a 32-channel photodetector

Despite recent progress in cell‐analysis technology, rapid classification of cells remains a very difficult task. Among the techniques available, flow cytometry (FCM) is considered especially powerful, because it is able to perform multiparametric analyses of single biological particles at a high flow rate–up to several thousand particles per second. Moreover, FCM is nondestructive, and flow cytometric analysis can be performed on live cells. The current limit for simultaneously detectable fluorescence signals in FCM is around 8–15 depending upon the instrument. Obtaining multiparametric measurements is a very complex task, and the necessity for fluorescence spectral overlap compensation creates a number of additional difficulties to solve. Further, to obtain well‐separated single spectral bands a very complex set of optical filters is required. This study describes the key components and principles involved in building a next‐generation flow cytometer based on a 32‐channel PMT array detector, a phase‐volume holographic grating, and a fast electronic board. The system is capable of full‐spectral data collection and spectral analysis at the single‐cell level. As demonstrated using fluorescent microspheres and lymphocytes labeled with a cocktail of antibodies (CD45/FITC, CD4/PE, CD8/ECD, and CD3/Cy5), the presented technology is able to simultaneously collect 32 narrow bands of fluorescence from single particles flowing across the laser beam in <5 μs. These 32 discrete values provide a proxy of the full fluorescence emission spectrum for each single particle (cell). Advanced statistical analysis has then been performed to separate the various clusters of lymphocytes. The average spectrum computed for each cluster has been used to characterize the corresponding combination of antibodies, and thus identify the various lymphocytes subsets. The powerful data‐collection capabilities of this flow cytometer open up significant opportunities for advanced analytical approaches, including spectral unmixing and unsupervised or supervised classification.

Discovering the unknown: detection of emerging pathogens using a label-free light-scattering system

A recently introduced technique for pathogen recognition called BARDOT (BActeria Rapid Detection using Optical scattering Technology) belongs to the broad class of optical sensors and relies on forward‐scatter phenotyping (FSP). The specificity of FSP derives from the morphological information that bacterial material encodes on a coherent optical wavefront passing through the colony. The system collects elastically scattered light patterns that, given a constant environment, are unique to each bacterial species and serovar. The notable similarity between FSP technology and spectroscopies is their reliance on statistical machine learning to perform recognition. Currently used methods utilize traditional supervised techniques which assume completeness of training libraries. However, this restrictive assumption is known to be false for most experimental conditions, resulting in unsatisfactory levels of accuracy, poor specificity, and consequently limited overall performance for biodetection and classification tasks. The presented work demonstrates application of the BARDOT system to classify bacteria belonging to the Salmonella class in a nonexhaustive framework, that is, without full knowledge about all the possible classes that can be encountered. Our study uses a Bayesian approach to learning with a nonexhaustive training dataset to allow for the automated detection of unknown bacterial classes.

Computational analysis of high-throughput flow cytometry data.

Introduction: Flow cytometry has been around for over 40 years, but only recently has the opportunity arisen to move into the high-throughput domain. The technology is now available and is highly competitive with imaging tools under the right conditions. Flow cytometry has, however, been a technology that has focused on its unique ability to study single cells and appropriate analytical tools are readily available to handle this traditional role of the technology. Areas covered: Expansion of flow cytometry to a high-throughput (HT) and high-content technology requires both advances in hardware and analytical tools. The historical perspective of flow cytometry operation as well as how the field has changed and what the key changes have been discussed. The authors provide a background and compelling arguments for moving toward HT flow, where there are many innovative opportunities. With alternative approaches now available for flow cytometry, there will be a considerable number of new applications. These opportunities show strong capability for drug screening and functional studies with cells in suspension. Expert opinion: There is no doubt that HT flow is a rich technology awaiting acceptance by the pharmaceutical community. It can provide a powerful phenotypic analytical toolset that has the capacity to change many current approaches to HT screening. The previous restrictions on the technology, based on its reduced capacity for sample throughput, are no longer a major issue. Overcoming this barrier has transformed a mature technology into one that can focus on systems biology questions not previously considered possible.

An excitation wavelength–scanning spectral imaging system for preclinical imaging

Small-animal fluorescence imaging is a rapidly growing field, driven by applications in cancer detection and pharmaceutical therapies. However, the practical use of this imaging technology is limited by image-quality issues related to autofluorescence background from animal tissues, as well as attenuation of the fluorescence signal due to scatter and absorption. To combat these problems, spectral imaging and analysis techniques are being employed to separate the fluorescence signal from background autofluorescence. To date, these technologies have focused on detecting the fluorescence emission spectrum at a fixed excitation wavelength. We present an alternative to this technique, an imaging spectrometer that detects the fluorescence excitation spectrum at a fixed emission wavelength. The advantages of this approach include increased available information for discrimination of fluorescent dyes, decreased optical radiation dose to the animal, and ability to scan a continuous wavelength range instead of discrete wavelength sampling. This excitation-scanning imager utilizes an acousto-optic tunable filter (AOTF), with supporting optics, to scan the excitation spectrum. Advanced image acquisition and analysis software has also been developed for classification and unmixing of the spectral image sets. Filtering has been implemented in a single-pass configuration with a bandwidth (full width at half maximum) of 16 nm at 550 nm central diffracted wavelength. We have characterized AOTF filtering over a wide range of incident light angles, much wider than has been previously reported in the literature, and we show how changes in incident light angle can be used to attenuate AOTF side lobes and alter bandwidth. A new parameter, in-band to out-of-band ratio, was defined to assess the quality of the filtered excitation light. Additional parameters were measured to allow objective characterization of the AOTF and the imager as a whole. This is necessary for comparing the excitation-scanning imager to other spectral and fluorescence imaging technologies. The effectiveness of the hyperspectral imager was tested by imaging and analysis of mice with injected fluorescent dyes. Finally, a discussion of the optimization of spectral fluorescence imagers is given, relating the effects of filter quality on fluorescence images collected and the analysis outcome.

High-Throughput Secondary Screening at the Single-Cell Level

We have developed an automated system for drug screening using a single-cell–multiple functional response technology. The approach uses a semiautomated preparatory system, high-speed sample collection, and a unique analytical tool that provides instantaneous results for compound dilutions using 384-well plates. The combination of automation and rapid robotic sampling increases quality control and robustness. High-speed flow cytometry is used to collect single-cell results together with a newly defined analytical tool for extraction of IC50 curves for multiple assays per cell. The principal advantage is the extreme speed of sample collection, with results from a 384-well plate being completed for both collection and data processing in less than 10 min. Using this approach, it is possible to extract detailed drug response information in a highly controlled fashion. The data are based on single-cell results, not populations. With simultaneous assays for different functions, it is possible to gain a more detailed understanding of each drug/compound interaction. Combined with integrated advanced data processing directly from raw data files, the process from sampling to analytical results is highly intuitive. Direct PubMed links allow review of drug structure and comparisons with similar compounds.

Portable bacterial identification system based on elastic light scatter patterns

BackgroundConventional diagnosis and identification of bacteria requires shipment of samples to a laboratory for genetic and biochemical analysis. This process can take days and imposes significant delay to action in situations where timely intervention can save lives and reduce associated costs. To enable faster response to an outbreak, a low-cost, small-footprint, portable microbial-identification instrument using forward scatterometry has been developed.ResultsThis device, weighing 9 lb and measuring 12 × 6 × 10.5 in., utilizes elastic light scatter (ELS) patterns to accurately capture bacterial colony characteristics and delivers the classification results via wireless access. The overall system consists of two CCD cameras, one rotational and one translational stage, and a 635-nm laser diode. Various software algorithms such as Hough transform, 2-D geometric moments, and the traveling salesman problem (TSP) have been implemented to provide colony count and circularity, centering process, and minimized travel time among colonies.ConclusionsExperiments were conducted with four bacteria genera using pure and mixed plate and as proof of principle a field test was conducted in four different locations where the average classification rate ranged between 95 and 100%.

Development of a microbial high-throughput screening instrument based on elastic light scatter patterns

A microbial high-throughput screening (HTS) system was developed that enabled high-speed combinatorial studies directly on bacterial colonies. The system consists of a forward scatterometer for elastic light scatter (ELS) detection, a plate transporter for sample handling, and a robotic incubator for automatic incubation. To minimize the ELS pattern-capturing time, a new calibration plate and correction algorithms were both designed, which dramatically reduced correction steps during acquisition of the circularly symmetric ELS patterns. Integration of three different control software programs was implemented, and the performance of the system was demonstrated with single-species detection for library generation and with time-resolved measurement for understanding ELS colony growth correlation, using Escherichia coli and Listeria. An in-house colony-tracking module enabled researchers to easily understand the time-dependent variation of the ELS from identical colony, which enabled further analysis in other biochemical experiments. The microbial HTS system provided an average scan time of 4.9 s per colony and the capability of automatically collecting more than 4000 ELS patterns within a 7-h time span.

A Statistical Modeling Approach to Computer-Aided Quantification of Dental Biofilm

Biofilm is a formation of microbial material on tooth substrata. Several methods to quantify dental biofilm coverage have recently been reported in the literature, but at best they provide a semiautomated approach to quantification with significant input from a human grader that comes with the graders bias of what is foreground, background, biofilm, and tooth. Additionally, human assessment indices limit the resolution of the quantification scale; most commercial scales use five levels of quantification for biofilm coverage (0%, 25%, 50%, 75%, and 100%). On the other hand, current state-of-the-art techniques in automatic plaque quantification fail to make their way into practical applications owing to their inability to incorporate human input to handle misclassifications. This paper proposes a new interactive method for biofilm quantification in Quantitative light-induced fluorescence (QLF) images of canine teeth that is independent of the perceptual bias of the grader. The method partitions a QLF image into segments of uniform texture and intensity called superpixels; every superpixel is statistically modeled as a realization of a single 2-D Gaussian Markov random field (GMRF) whose parameters are estimated; the superpixel is then assigned to one of three classes ( background, biofilm, tooth substratum) based on the training set of data. The quantification results show a high degree of consistency and precision. At the same time, the proposed method gives pathologists full control to postprocess the automatic quantification by flipping misclassified superpixels to a different state (background, tooth, biofilm) with a single click, providing greater usability than simply marking the boundaries of biofilm and tooth as done by current state-of-the-art methods.

Multispectral Flow Cytometry: Next Generation Tools for Automated Classification

Flow cytometry has moved from a relatively simple technology 30 years ago, to a very sophisticated and high-speed detection technology today. However, the number of simultaneous fluorescence dyes that can be separated is limited by the difficulty in overlapping spectra and the complexity of resolving this spectral overlap problem. High-speed multianode PMTs may change this situation. The system we propose utilizes such a technology to allow full spectral analysis of cells and particles as they flow past the light source. Making these measurements is very complex and the necessity for advanced spectral overlap calculations creates a number of difficult problems to solve in a very short period of time. Next-generation instruments can either increase the number of detectors or modify the principles of collection. If the detector system were simplified, the overall cost and complexity of single-cell analytical systems might be reduced. This requires changes in both hardware and software that allow for the analysis of 30 or more spectral signals. Analysis of complex data sets requires some completely new analytical approaches, particularly in the area of multispectral analysis. This presentation discusses a next-generation instrument, which can collect simultaneously 32 bands of fluorescence from a particle in less than 5 microseconds. This opens new opportunities for analysis of bioparticles in a very fast and high content fashion.