Automated analysis of the cytokinesis-block micronucleus assay for radiation biodosimetry using imaging flow cytometry

The cytokinesis-block micronucleus (CBMN) assay is employed in biological dosimetry to determine the dose of radiation to an exposed individual from the frequency of micronuclei (MN) in binucleated lymphocyte cells. The method has been partially automated for the use in mass casualty events, but it would be advantageous to further automate the method for increased throughput. Recently, automated image analysis has been successfully applied to the traditional, slide-scoring-based method of the CBMN assay. However, with the development of new technologies such as the imaging flow cytometer, it is now possible to adapt this microscope-based assay to an automated imaging flow cytometry method. The ImageStream^X is an imaging flow cytometer that has adequate sensitivity to quantify radiation doses larger than 1 Gy while adding the increased throughput of traditional flow cytometry. The protocol and analysis presented in this work adapts the CBMN assay for the use on the ImageStream^X. Ex vivo-irradiated whole blood samples cultured for CBMN were analyzed on the ImageStream^X, and preliminary results indicate that binucleated cells and MN can be identified, imaged and enumerated automatically by imaging flow cytometry. Details of the method development, gating strategy and the dose response curve generated are presented and indicate that adaptation of the CBMN assay for the use with imaging flow cytometry has potential for high-throughput analysis following a mass casualty radiological event.     

A picture is worth a thousand words: Genomics to phenomics in the yeast Saccharomyces cerevisiae

Large scale cell biological experiments are beginning to be applied as a systems-level approach to decipher mechanisms that govern cellular function in health and disease. The use of automated microscopes combined with digital imaging, machine learning and other analytical tools has enabled high-content screening (HCS) in a variety of experimental systems. Successful HCS screens demand careful attention to assay development, data acquisition methods and available genomic tools. In this minireview, we highlight developments in this field pertaining to yeast cell biology and discuss how we have combined HCS with methods for automated yeast genetics (synthetic genetic array (SGA) analysis) to enable systematic analysis of cell biological phenotypes in a variety of genetic backgrounds.     

Determination of drugs in biological fluids by direct injection of samples for liquid-chromatographic analysis

The analysis of drugs in various biological fluids is an important criterion for the determination of the physiological performance of a drug. After sampling of the biological fluid, the next step in the analytical process is sample preparation. The complexity of biological fluids adds to the challenge of direct determination of the drug by chromatographic analysis, therefore demanding a sample preparation step that is often time-consuming, tedious, and frequently overlooked. However, direct on-line injection methods offer the advantage of reducing sample preparation steps and enabling effective pre-concentration and clean-up of biological fluids. These procedures can be automated and therefore reduce the requirements for handling potentially infectious biomaterial, improve reproducibility, and minimize sample manipulations and potential contamination.The objective of this review is to present an overview of the existing literature with emphasis on advances in automated sample preparation methods for liquid-chromatographic methods. More specifically, this review concentrates on the use of direct injection techniques, such as restricted-access materials, turbulent-flow chromatography and other automated on-line solid-phase extraction (SPE) procedures. It also includes short overviews of emerging automated extraction-phase technologies, such as molecularly imprinted polymers, in-tube solid-phase micro-extraction, and micro-extraction in a packed syringe for a more selective extraction of analytes from complex samples, providing further improvements in the analysis of biological materials. Lastly, the outlook for these methods and potential new applications for these technologies are briefly discussed.     

Determination of drugs in biological fluids by direct injection of samples for liquid-chromatographic analysis

The analysis of drugs in various biological fluids is an important criterion for the determination of the physiological performance of a drug. After sampling of the biological fluid, the next step in the analytical process is sample preparation. The complexity of biological fluids adds to the challenge of direct determination of the drug by chromatographic analysis, therefore demanding a sample preparation step that is often time-consuming, tedious, and frequently overlooked. However, direct on-line injection methods offer the advantage of reducing sample preparation steps and enabling effective pre-concentration and clean-up of biological fluids. These procedures can be automated and therefore reduce the requirements for handling potentially infectious biomaterial, improve reproducibility, and minimize sample manipulations and potential contamination. The objective of this review is to present an overview of the existing literature with emphasis on advances in automated sample preparation methods for liquid-chromatographic methods. More specifically, this review concentrates on the use of direct injection techniques, such as restricted-access materials, turbulent-flow chromatography and other automated on-line solid-phase extraction (SPE) procedures. It also includes short overviews of emerging automated extraction-phase technologies, such as molecularly imprinted polymers, in-tube solid-phase micro-extraction, and micro-extraction in a packed syringe for a more selective extraction of analytes from complex samples, providing further improvements in the analysis of biological materials. Lastly, the outlook for these methods and potential new applications for these technologies are briefly discussed.     

Combinatorial biochemistry in plants: the case of O-methyltransferases

Combinatorial chemistry is common place today in chemical synthesis. Virtually thousands of derivatives of a molecule can be achieved by automated systems. The use of biological systems to exploit combinatorial chemistry (combinatorial biochemistry) now has multiple examples in the polyketide field. The modular functional domain structure of polyketide synthases have been recombined through genetic engineering into unnatural constellations in heterologous hosts in order to produce polyketide structures not yet discovered in nature. We present herein an example for a potential type of combinatorial biochemistry in alkaloidal systems using various combinations of Thalictrum tuberosum (meadow rue) O-methyltransferase subunits that result in heterodimeric enzymes with substrate specificities that differ from those of the homodimeric native enzymes.     

New developments in automated cytogenetic imaging: unattended scoring of dicentric chromosomes, micronuclei, single cell gel electrophoresis, and fluorescence signals

The quantification of DNA damage, both in vivo and in vitro, can be very time consuming, since large amounts of samples need to be scored. Additional uncertainties may arise due to the lack of documentation or by scoring biases. Image analysis automation is a possible strategy to cope with these difficulties and to generate a new quality of reproducibility. In this communication we collected some recent results obtained with the automated scanning platform Metafer, covering applications that are being used in radiation research, biological dosimetry, DNA repair research and environmental mutagenesis studies. We can show that the automated scoring for dicentric chromosomes, for micronuclei, and for Comet assay cells produce reliable and reproducible results, which prove the usability of automated scanning in the above mentioned research fields.     

微核技术研究进展

微核试验作为检测染色体损伤最常用而有效的细胞遗传学检测方法之一,经济、简便、快速,在敏感性、特异性和准确性方面,与经典的染色体畸变分析方法基本相当。主要综述国内外微核检测技术的最新研究进展,尤其是微核的自动化检测技术。其中流式细胞仪自动化检测和激光扫描细胞仪自动化检测,以及微核试验高内涵筛选方法由于其特有的优势,应用和发展前景广阔。     

Automated flow cytometry for monitoring CHO cell cultures

Flow cytometry has been used to accurately monitor cell events that indicate the spatio-temporal state of a bioreactor culture. The introduction of process analytical technology (PAT) has led to process improvements using real-time or semi real-time monitoring systems. Integration of flow cytometry into an automated scheme for improved process monitoring can benefit PAT in bioreactor-based biopharmaceutical productions by establishing optimum process conditions and better quality protocols. Herein, we provide detailed protocols for establishing an automated flow cytometry system that can be used to investigate and monitor cell growth, viability, cell size, and cell cycle data. A method is described for the use of such a system primarily focused on CHO cell culture, although it is foreseen the information gathered from automated flow cytometry can be applied to a variety of cell lines to address both PAT requirements and gain further understanding of complex biological systems.     

Comparison of manual and automated methods for identifying target sounds in audio recordings of Pileated, Pale-billed, and putative Ivory-billed woodpeckers

ABSTRACT.   Although offering many benefits over manual recording and survey techniques for avian field studies, automated sound recording systems produce large datasets that must be carefully examined to locate sounds of interest. We compared two methods for locating target sounds in continuous sound recordings: (1) a manual method using computer software to provide a visual representation of the recording as a sound spectrogram and (2) an automated method using sound analysis software preprogrammed to identify specific target sounds. For both methods, we examined the time required to process a 24-h recording, scanning accuracy, and scanning comprehensiveness using four different target sounds of Pileated Woodpeckers ( Dryocopus pileatus ), Pale-billed Woodpeckers ( Campephilus guatemalensis ), and putative Ivory-billed Woodpeckers ( Campehilus principalis ). We collected recordings from the bottomland forests of Florida and the Neotropical dry forests of Costa Rica, and compared manual versus automated cross-correlation scanning techniques. The automated scanning method required less time to process sound recordings, but made more false positive identifications and was less comprehensive than the manual method, identifying significantly fewer target sounds. Although the automated scanning method offers a fast and economic alternative to traditional manual efforts, our results indicate that manual scanning is best for studies requiring an accurate account of temporal patterns in call frequency and for those involving birds with low vocalization rates.     

Selective determination of lithium in biological fluids using flow injection analysis

The use of flow injection analysis to automated extraction methods for the determination of lithium ion utilizing crown ethers or cryptands is demonstrated. The ion-pair extraction of cryptand 211, lithium, and resazurin exhibits a linear range for lithium ion of 70 ppb to 2.1 ppm. This method could tolerate up to 1000 ppm sodium ion. The chromogenic crown ether, 1-(2-hydroxy-5-nitrobenzyl)-1-aza-4,7,10-trioxacyclododecane, exhibits a linear range for lithium ion of 0.3 to 2 ppm. A sodium ion concentration of 230 ppm can be tolerated. Both extraction systems were used in the automated determination of lithium in blood serum and urine. Both methods agreed well with the known and/or atomic absorption values.     

Comparison of bioactivity between GSM 900 MHz and DCS 1800 MHz mobile telephony radiation

An increasing number of studies find that pulsed Radio Frequency (RF), electromagnetic radiation of both systems of digital mobile telephony, established and commonly used in Europe during the last years, GSM 900 MHz (Global System for Mobile telecommunications) and DCS 1800 MHz (Digital Cellular System), exert intense biological action on different organisms and cells (Hardell et al., 2006; Hyland, 2000; Kundi, 2004; Panagopoulos et al., 2004, 2007). The two types of cellular telephony radiation use different carrier frequencies and give different frequency spectra, but they usually also differ in intensity, as GSM 900 MHz antennas operate at about double the power output than the corresponding DCS 1800 MHz ones. In our present experiments, we used a model biological system, the reproductive capacity of Drosophila melanogaster, to compare the biological activity between the two systems of cellular mobile telephony radiation. Both types of radiation were found to decrease significantly and non thermally the insect's reproductive capacity, but GSM 900 MHz seems to be even more bioactive than DCS 1800 MHz. The difference seems to be dependent mostly on field intensity and less on carrier frequency.     

A line-balancing strategy for designing flexible assembly systems

We present a rough-cut analysis tool that quickly determines a few potential cost-effective designs at the initial design stage of flexible assembly systems (FASs) prior to a detailed analysis such as simulation. It uses quantitative methods for selecting and configuring the components of an FAS suitable for medium to high volumes of several similar products. The system is organized as a series of assembly stations linked with an automated material-handling system moving parts in a unidirectional flow. Each station consists of a single machine or of identical parallel machines. The methods exploit the ability of flexible hardware to switch almost instantaneously from product to product. Our approach is particularly suitable where the product mix is expected to be stable, since we combine the hardware-configuration phase with the task-allocation phase. For the required volume of products, we use integer programming to select the number of stations and the number of machines at each station and to allocate tasks to stations. We use queueing network analysis, which takes into account the mean and variance of processing times among different products to determine the necessary capacity of the material-handling system. We iterate between the two analyses to find the combined solution with the lowest costs. Work-in-process costs are also included in the analysis. Computational results are presented.     

Computerized quantification of immunofluorescence-labeled axon terminals and analysis of co-localization of neurochemicals in axon terminals with a confocal scanning laser microscope

The confocal scanning laser microscope (CSLM) offers improved optical resolution and contrast, high photometric precision, and the ability to make optical sections. These benefits were explored for use in quantitative analysis of immunofluorescence-labeled axon terminals. Guidelines were obtained for adjustments of the CSLM parameters. In the present applications, bleaching of the fluorescence did not represent a serious obstacle to analysis with the CSLM. A method was developed to distinguish the background fluorescence from the specific fluorescence labeling. This procedure made way for the development of automated quantification of immunolabeled axon terminals. The automated procedures substantially reduced the man-hour expenditure for analysis and provided highly reproducible quantifications compared with manual methods. The increased resolution and contrast of the CSLM allowed measurements of the fluorescence signal strength of individual axon terminals. The CSLM also allowed detection of co-localized neurochemicals in axon terminals.     

Transgene flow in Mexican maize revisited: Socio‐biological analysis across two contrasting farmer communities and seed management systems

The flow of transgenes into landraces and wild relatives is an important biosafety concern. The case of transgene flow into local maize varieties in Mexico (the center of origin of maize) has been intensively debated over the past 15 years, including legal, political, and environmental disputes fanned by the existence of a significant scientific controversy over the methods used for the detection of transgenes. The use of diverse approaches and a lack of harmonized methods specific to the detection and monitoring of transgenes in landraces have generated both positive and negative results regarding contamination of Mexican maize with genetically modified material over the years. In this paper, we revisit the case of transgene contamination in Mexican maize and present a novel research approach based on socio‐biological analysis of contrasting communities and seed management systems. Two communities were used to investigate how different social and biological factors can affect transgene flow and impact transgene spread in Mexico. Our results show the presence of transgenes in one community and thus support the position that transgenes are highly likely to be present in Mexican maize landraces. However, our work also demonstrates that the extent and frequency with which transgenes can be found will significantly depend on the societal characteristics and seed management systems of the local communities. Therefore, we argue that future analysis of transgene presence should include social research on the seed management practices in the sampling area so that more robust and comprehensive understandings and conclusions can be drawn.     

Pattern recognition software and techniques for biological image analysis

The increasing prevalence of automated image acquisition systems is enabling new types of microscopy experiments that generate large image datasets. However, there is a perceived lack of robust image analysis systems required to process these diverse datasets. Most automated image analysis systems are tailored for specific types of microscopy, contrast methods, probes, and even cell types. This imposes significant constraints on experimental design, limiting their application to the narrow set of imaging methods for which they were designed. One of the approaches to address these limitations is pattern recognition, which was originally developed for remote sensing, and is increasingly being applied to the biology domain. This approach relies on training a computer to recognize patterns in images rather than developing algorithms or tuning parameters for specific image processing tasks. The generality of this approach promises to enable data mining in extensive image repositories, and provide objective and quantitative imaging assays for routine use. Here, we provide a brief overview of the technologies behind pattern recognition and its use in computer vision for biological and biomedical imaging. We list available software tools that can be used by biologists and suggest practical experimental considerations to make the best use of pattern recognition techniques for imaging assays.     

Automated Processing of Imaging Data through Multi-tiered Classification of Biological Structures Illustrated Using Caenorhabditis elegans

Quantitative imaging has become a vital technique in biological discovery and clinical diagnostics; a plethora of tools have recently been developed to enable new and accelerated forms of biological investigation. Increasingly, the capacity for high-throughput experimentation provided by new imaging modalities, contrast techniques, microscopy tools, microfluidics and computer controlled systems shifts the experimental bottleneck from the level of physical manipulation and raw data collection to automated recognition and data processing. Yet, despite their broad importance, image analysis solutions to address these needs have been narrowly tailored. Here, we present a generalizable formulation for autonomous identification of specific biological structures that is applicable for many problems. The process flow architecture we present here utilizes standard image processing techniques and the multi-tiered application of classification models such as support vector machines (SVM). These low-level functions are readily available in a large array of image processing software packages and programming languages. Our framework is thus both easy to implement at the modular level and provides specific high-level architecture to guide the solution of more complicated image-processing problems. We demonstrate the utility of the classification routine by developing two specific classifiers as a toolset for automation and cell identification in the model organism Caenorhabditis elegans. To serve a common need for automated high-resolution imaging and behavior applications in the C. elegans research community, we contribute a ready-to-use classifier for the identification of the head of the animal under bright field imaging. Furthermore, we extend our framework to address the pervasive problem of cell-specific identification under fluorescent imaging, which is critical for biological investigation in multicellular organisms or tissues. Using these examples as a guide, we envision the broad utility of the framework for diverse problems across different length scales and imaging methods.