Automation Highlights from the Literature

Small Molecules of Different Origins Have Distinct Distributions of Structural Complexity That Correlate with Protein-Binding Profiles

Using a diverse collection of small molecules generated from a variety of sources, Clemons et al. from the Broad Institute measure protein-binding activities of each individual compound against each of 100 diverse (sequence-unrelated) proteins using small-molecule microarrays. They also analyze structural features, including complexity, of the small molecules. They find that compounds from different sources (commercial, academic, natural) have different protein-binding behaviors and that these behaviors correlate with general trends in stereochemical and shape descriptors for these compound collections. Increasing the content of sp(3)-hybridized and stereogenic atoms relative to compounds from commercial sources, which compose of the majority of current screening collections, improves binding selectivity and frequency. The results suggest structural features that synthetic chemists can target when synthesizing screening collections for biological discovery. Because binding proteins selectively can be a key feature of high-value probes and drugs, synthesizing compounds having features identified in this study may result in improved performance of screening collections (Clemons, P. A., et al. Proc. Natl. Acad. Sci. 2010, 107(44), 18787–18792).

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Tal V. Murthy, Ph.D. Caliper Life Sciences Hopkinton, MA

Automation in the High-Throughput Selection of Random Combinatorial Libraries: Different Approaches for Select Applications

Automation in combination with high-throughput screening methods has revolutionized molecular biology in the last two decades. Today, many combinatorial libraries and several systems for automation are available. Depending on scope, budget, and time, a different combination of library and experimental handling might be most effective. In this review, the authors discuss several concepts of combinatorial libraries and provide information as what to expect from these depending on the given context (Gloker, J. Molecules, 2010, 15(4), 2478–2490).

Validation of Multiplex Microbead Immunoassay for Simultaneous Serodetection of Multiple Infectious Agents in Laboratory Mice

Multiplex methodologies enable simultaneous detection of antibodies against several infectious agents allowing sample conservation, cost effectiveness, and amenability to high-throughput/automation. The authors previously described a multiplex microbead immunoassay for serodetection of 10, high-priority mouse infectious pathogens. Here, they present a validation of this multiplex diagnostic system using approximately 400 serum samples from different groups of mice. Computer-assisted multivariate analysis of the resulting high-volume data (8000 data points) is performed. This computational approach enables presentation of data in a variety of easily in-terpretable formats (e.g., correlation tables and heat maps). Importantly, this computer-aided approach is instrumental for the evaluation of assay accuracy, sensitivity, specificity, and robustness during the study. Crucial pieces of information are obtained to make timely adjustments for assay refinement. This progressive approach to developing an implementation-ready clinical assay, facilitated by computational analysis, produces a highly efficient, accurate, and dependable serodiagnostics system. This system effectively replaces the current state-of-the-art methodology (ELISA) used in mouse colony health management at the University of California and the Jackson Laboratory. The pathway to develop multiplex serology tests for infectious disease diagnosis described here serves as a model for multiplex immunoassay design, clinical validation, refinement, and implementation (Ravindran, R., et al. J. Immunol. Methods. 2010, 363(1), 51–59).

Droplet Microfluidics: Recent Developments and Future Applications

In this publication, the authors report recent advances in the field of droplet-based microfluidics. Specifically, they highlight the unique features of such platforms for high-throughput experimentation; describe functional components that afford complex analytical processing and report on applications in synthesis, high-throughput screening, cell biology, and synthetic and systems biology. Issues including the integration of high-information content detection methods, long-term droplet stability, and opportunities for large-scale and intelligent biological experimentation are also discussed (Casadevall, I. Chem. Commun. (Camb). 2011, 47(7), 1936–1942).

Microfluidic Devices for Bioapplications

Harnessing the ability to precisely and reproducibly actuate fluids and manipulate bioparticles such as DNA, cells, and molecules at the microscale, microfluidics is a powerful tool that is currently revolutionizing chemical and biological analysis by replicating laboratory bench-top technology on a miniature chip-scale device, thus allowing assays to be carried out at a fraction of the time and cost while affording portability and field-use capability. Emerging from a decade of research and development in microfluidic technology are a wide range of promising laboratory and consumer biotechnological applications from microscale genetic and proteomic analysis kits, cell culture and manipulation platforms, biosensors, pathogen detection systems for point-of-care diagnostic devices, high-throughput combinatorial drug screening platforms, schemes for targeted drug delivery and advanced therapeutics, and novel biomaterials synthesis for tissue engineering. The developments associated with these technological advances along with their respective applications to date are reviewed from a broad perspective and possible future directions that could arise from the current state of the art are discussed (Yeo, L. Y., et al. Small 2011, 7(1), 12–48).

Rapid Whole-Cell Sensing Chip for Low-Level Arsenite Detection

A novel whole-cell sensing chip system consisting of a microconcentrator, a set of electrochemical detection electrodes and a microfluidic channel is developed for rapid detection of arsenite in water. Firstly, the Escherichia coli cells transformed with arsenited-regulated reporter plasmids are incubated with solution-contained arsenite. Under this condition, the level of reporter protein, β-galactosidase, expressed by E. coli cells is dependent on the concentration of arsenite. Using the dielectrophoretic force, the microconcentrator continuously enriches the E. coli cells into a small area above the embedded detection electrodes. Then, the relative expression levels of β-galactosidase are obtained using the electrochemical method to measure the amount of p-aminophenol, which is converted from the p-aminophenyl-β-D-galactopyranoside by β-galactosidase. The result indicates this device can detect as little as 0.1 ppm of arsenite within 30 min. Compared with other traditional detection methods, this new device provides better performance in terms of higher sensitivity, shorter analysis time, and lower cost in detecting the arsenite (Chiou, C.H., et al. Biosens. Bioelectron. 2011, 26(5), 2484–2488).

Systems Biology Approaches and Tools for Analysis of Interactomes and Multitarget Drugs

Systems biology is essentially a proteomic and epigenetic exercise because the relatively condensed information of genomes unfolds on the level of proteins. The flexibility of cellular architectures is not only mediated by a dazzling number of proteinaceous species but by the kinetics of their molecular changes. The time scales of posttranslational modifications range from milliseconds to years. The genetic framework of an organism only provides the blue print of protein embodiments, which are constantly shaped by external input. Indeed, posttranslational modifications of proteins represent the scope and velocity of these inputs and fulfill the requirements of integration of external spatiotemporal signal transduction inside an organism.

The optimization of biochemical networks for this type of information processing and storage results chemically in extremely fine-tuned molecular entities. The huge dynamic range of concentrations, the chemical diversity, and the necessity of synchronization of complex protein expression patterns pose a major challenge to systemic analysis of biological models. One further message is that many of the key reactions in living systems are essentially based on interactions of moderate affinities and moderate selectivities. This principle is responsible for enormous flexibility and redundancy of cellular circuitries. In complex disorders such as cancer or neurodegenerative diseases, which initially appear to be rooted in relatively subtle dysfunctions of multimodal physiologic pathways, drug discovery programs based on the concept of high-affinity/high-specificity compounds (“one target, one disease”), which has been dominating the pharmaceutical industry for a long time, increasingly turn out to be unsuccessful. Despite improvements in rational drug design and high-throughput screening methods, the number of novel, single-target drugs fell much behind expectations during the past decade, and the treatment of complex diseases remains a most pressing medical need.

Currently, a change of paradigm can be observed with regard to a new interest in agents that modulate multiple targets simultaneously, essentially “dirty drugs.” Targeting cellular function as a system rather than on the level of the single target, significantly increases the size of the drugable proteome and is expected to introduce novel classes of multi-target drugs with fewer adverse effects and toxicity. Multiple target approaches have recently been used to design medications against atherosclerosis, cancer, depression, psychosis, and neurodegenerative diseases. A focused approach toward systemic drugs will certainly require the development of novel computational and mathematical concepts for appropriate modeling of complex data, but the key is the extraction of relevant molecular information from biological systems by implementing rigid statistical procedures to differential proteomic analytics (Schrattenholz, A., et al. Methods Mol. Biol. 2010, 662, 29–58).

Benchmarking Glucose Results Through Automation: The 2009 Remote Automated Laboratory System Report

Hyperglycemia in the adult inpatient population remains a topic of intense study in U.S. hospitals. Most hospitals have established glycemic control programs but are unable to determine their impact. The 2009 Remote Automated Laboratory System (RALS) Report provides trends in glycemic control over 4 years to 576 U.S. hospitals to support their effort to manage inpatient hyperglycemia.

A proprietary software application feeds deidentified patient point-of-care blood glucose (POC-BG) data from the Medical Automation Systems' RALS-Plus data management system to a central server. Analyses include the number of tests and the mean and median BG results for intensive care unit (ICU), non-ICU, and each hospital compared with the aggregate of the other hospitals. More than 175 million BG results are extracted from 2006 to 2009; 25% are from the ICU. Mean range of BG results for all inpatients in 2006, 2007, 2008, and 2009 is 142.2–201.9, 145.6–201.2, 140.6–205.7, and 140.7–202.4 mg/dL, respectively. The range for ICU patients is 128–226.5, 119.5–219.8, 121.6–226.0, and 121.1–217 mg/dL, respectively. The range for non-ICU patients is 143.4–195.5, 148.6–199.8, 145.2–201.9, and 140.7–203.6 mg/dL, respectively. Hyperglycemia rates of >180 mg/dL in 2008 and 2009 are examined, and hypoglycemia rates of <40 mg/dL (severe) and <70 mg/dL (moderate) in both 2008 and 2009 are calculated.

From these data, hospitals can determine the current state of glycemic control in their hospitals and when compared with other hospitals. For many, glycemic control has improved. Automated POC-BG data management software can assist in this effort (Anderson, M., et al. J. Diabetes Sci. Technol. 2010, 4(6), 1507–1513).

Laser Scanning Cytometry for Automation of the Micronucleus Assay

Laser scanning cytometry (LSC) provides a novel approach for automated scoring of micronuclei (MN) in different types of mammalian cells, serving as a biomarker of genotoxicity and mutagenicity. In this review, Darzynkiewicz, Z., et al. discuss the advances to date in measuring MN in cell lines, buccal cells, and erythrocytes; describe the advantages; and outline potential challenges of this distinctive approach of analysis of nuclear anomalies. The use of multiple laser wavelengths in LSC and the high dynamic range of fluorescence and absorption detection allow simultaneous measurement of multiple cellular and nuclear features such as cytoplasmic area, nuclear area, DNA content and density of nuclei and MN, protein content and density of cytoplasm, and other features using molecular probes. This high-content analysis approach allows the cells of interest to be identified (e.g., binucleated cells in cytokinesis-blocked cultures) and MN scored specifically in them. MN assays in cell lines (e.g., the CHO cell MN assay) using LSC are increasingly used in routine toxicology screening. More high-content MN assays and the expansion of MN analysis by LSC to other models (exfoliated cells, dermal cell models, and so on) hold great promise for robust and exciting developments in MN assay automation as a high-content high-throughput analysis procedure (Mutagenesis 2011, 26(1), 153–161).

Contextual Automated 3D Analysis of Subcellular Organelles Adapted to High-Content Screening

Advances in automated imaging microscopy allow fast acquisitions of multidimensional biological samples. Those microscopes open new possibilities for analyzing subcellular structures and spatial cellular arrangements. In this article, Dorval, T., et al. describe a 3D image analysis framework adapted to medium-throughput screening. On adaptive and regularized segmentation, followed by precise 3D reconstruction, they achieve automatic quantification of numerous relevant 3D descriptors related to the shape, texture, and fluorescence intensity of multiple-stained subcellular structures. A global analysis of the 3D reconstructed scene shows additional possibilities to quantify the relative position of organelles. Implementing this methodology, the authors analyze the subcellular reorganization of the nucleus, the Golgi apparatus, and the centrioles occurring during the cell cycle. In addition, they quantify the effect of a genetic mutation associated with the early onset primary dystonia on the redistribution of torsinA from the bulk endoplasmic reticulum to the perinuclear space of the nuclear envelope. The authors further show that their method enables the classification of various translocation levels of torsinA and opens the possibility for compound-based screening campaigns restoring the normal torsinA phenotype (J. Biomol. Screen. 2010, 15(7), 847–857).

High-Content, Image-Based Screening for Drug Targets in Yeast

Drug discovery and development are predicated on elucidation of the potential mechanisms of action and cellular targets of candidate chemical compounds. Recent advances in high-content imaging techniques allow simultaneous analysis of a range of cellular events. In this study, a novel strategy to identify drug targets by combining genetic screening and high-content imaging in yeast is proposed. In this approach, the authors infer the cellular functions affected by candidate drugs by comparing morphologic changes induced by the compounds with the phenotypes of yeast mutants. Using this method and four well-characterized reagents, the authors successfully identify previously known target genes of the compounds and other genes involved with functionally related cellular pathways. This is the first demonstration of a genetic high-content assay that can be used to identify drug targets based on morphologic phenotypes of a reference mutant panel (Ohnuki, S., et al. PLoS One 2010, 5(4), e10177).