Abstract
Laboratory Automation and High-Throughput Chemistry
Automated Microfluidic Protein lmmunoblotting
This protocol describes regional photopatterning of polyacrylamide gels in glass microfluidic devices as a platform for seamless integration of multiple assay steps. The technology enables rapid, automated protein immunoblotting, demonstrated in this study for native western blotting. The fabrication procedure is straightforward and requires approximately 3 h from the start of gel photopatterning to completion of native protein western blotting, a substantial time savings over slab-gel immunoblotting. The assay itself requires less than 5 min. Importantly, all assay stages are program-mably controlled by a high-voltage power supply and monitored by an epifluorescence microscope equipped with a charge-coupled device camera. This approach of M. He and A. E. Herr from University of California Berkeley, overcomes severe limitations associated with conventional immunoblotting, including multiple steps requiring manual intervention, low throughput, and substantial consumption of reagents. The authors also describe a simple chemical recycling protocol so that glass chips can be reused. The fabrication technique described forms the basis for a diverse suite of bioa-nalytical tools, including DNA/RNA blotting and multidimensional separations (He, M. and Herr, A. E. Nat. Protoc. 2010, 5(11), 1844-1856).
Fully Automated High-Quality NMR Structure Determination of Small (2)H-Enriched Proteins
Determination of high-quality small protein structures by nuclear magnetic resonance (NMR) methods generally requires acquisition and analysis of an extensive set of structural constraints. The process generally demands extensive backbone and side chain resonance assignments, and weeks or even months of data collection and interpretation. The authors, Y. Tang et al. demonstrate rapid and high-quality protein NMR structure generation using CS-Rosetta with a perdeuterated protein sample made at a significantly reduced cost using new bacterial culture condensation methods. Their strategy provides the basis for a high-throughput approach for routine, rapid, high-quality structure determination of small proteins.
As an example, the authors demonstrate the determination of a high-quality 3D structure of a small 8 kDa protein, E. coli cold shock protein A (CspA), using <4 days of data collection and fully automated data analysis methods together with CS-Rosetta. The resulting CspA structure is highly converged and in excellent agreement with the published crystal structure, with a backbone root mean square deviation (RMSD) value of 0.5 Å, an all atom RMSD value of 1.2 Å to the crystal structure for well-defined regions, and RMSD value of 1.1 Å to crystal structure for core, non—solvent-exposed side chain atoms. Cross validation of the structure with (15)N- and (13)C-edi-ted NOESY data obtained with a perdeuterated (15) N-, (13)C-enriched (13)CH(3) methyl protonated CspA sample confirms that essentially all of these independently interpreted NOE-based constraints are already satisfied in each of the 10 CS-Rosetta structures. By these criteria, the CS-Rosetta structure generated by fully automated analysis of data for a perdeuterated sample provides an accurate structure of CspA. This represents a general approach for rapid, automated structure determination of small proteins by NMR (Tang, Y. et al. J. Struct. Funct. Genomics 2010, 11(4), 223-232).
Microfluidic Chip Technology and Mlcroreactor Technology
Direct Plate-Reader Measurement of Nitric Oxide Released From Hypoxic Erythrocytes Flowing Through a Microfluidic Device
The ability to perform a fluorescence-based quantitative determination of a biologically important analyte directly released from mammalian cells using a standard microtiter plate reader to measure wells integrated into a microfluidic device is reported. Specifically, the amount of nitric oxide (NO) released from flowing erythrocytes (ERYs) exposed to a hypoxic buffer is measured using a fluorescein-based probe. The ERYs are pumped through channels in one layer of the poly(dimethylsiloxane) device; as these cells release NO, it flows through a porous polycarbonate membrane to the probe. The device is then placed into a standard microtiter plate reader for measurement, with the entire calibration and analyte determination occurring simultaneously. Using this method, NO release from hypoxic ERYs is determined to be 6.9 ± 1.8 microM, a significantly increased value in comparison to that from normoxic ERYs of 0.60 ± 0.04 microM (p < 0.001, n = 4 rabbits). Furthermore, the reproducibility (reported as a %RSD) of measuring fluorescence standards is 3.5%. Detection limits, dynamic range, and optimal membrane pore diameters are also reported. This device enables the use of a standard high-throughput tool (the plate reader) to measure analytes in a microfluidic device, the ability to improve the quantitative determination of a relatively unstable molecule (NO), and the incorporation of a flow component and blood constituent into a system that can be combined with microtiter plate technology (Halpin, S. T. and Spence, D. M. Anal. Chem.
Biological Applications of Microfluidic Gradient Devices
This review from National University of Seoul attempts to apply the principles of microfluidics engineering to cancer biology. These types of approaches allow biologists to efficiently use the concepts of engineering in their specific research. Molecular gradients play an important role in diverse physiological and pathological phenomena such as immune response, wound healing, development, and cancer metastasis. In the past 10 years, engineering tools have been increasingly used to develop experimental platforms that capture important aspects of cellular microenvironments to allow quantitative and reproducible characterization of cellular response to gradients. This review discusses the emergence of microfluidics-based gradient generators and their applications in enhancing our understanding of fundamental biological processes such as chemotaxis and morphogenesis. The principles and applications of microfluidic gradient generation in both 2D and 3D cellular microenvironments are discussed with emphasis on approaches to manipulate spatial and temporal distribution of signaling molecules (Kim, S. et al. Integr. Biol. (Camb).
Kinetics Studies of P-Cresol Biodegradation by Using Pseudomonas Putida in Batch Reactor and in Continuous Bioreactor Packed with Calcium Alginate Beads
This study deals with the biodegradation of p-cresol by using Pseudomonas putida in a batch reactor and a continuous bioreactor packed with calcium alginate beads. The maximum specific growth rate of 0.8121 h(-l) is obtained at 200 mg L(-l) concentration of p-cresol in batch reactor. The maximum p-cresol degradation rate is obtained 6.598 mg L(-l) h(-l) at S(o) = 200 mg L(-l) and 62.8 mg L(-l) h(-l) at S(o) = 500 mg L(-l) for batch reactor and a continuous bioreactor, respectively. The p-cresol degradation rate of continuous bioreactor is 9- to 10-fold higher than those of the batch reactor. It shows that the continuous bioreactor can tolerate a higher concentration of p-cresol. A Haldane model is also used for p-cresol inhibition in batch reactor and a modified equation similar to Haldane model for continuous bioreactor. The Haldane parameters are obtained as μ(max) 0.3398 h(-l), K(s) 110.9574 mg L(-l), and K(I) 497.6169 mg L(-l) in batch reactor. The parameters used in continuous bioreactor are obtained as D(max) 91.801 mg L(-l) h(-l), K(s) 131.292 mg L(-l), and K(I) 1217.7 mg L(-l). The value K(I) of continuous bioreactor is approximately 2.5 times higher than the batch reactor. Higher K(I) value of continuous bioreactor indicates P. putida can grow at high range of p-cresol concentration. The ability of tolerance of higher p-cresol concentrations may be one reason for biofilm attachment on the packed bed in the continuous operation (Mathur, A. K. et al. Water Sci. Technol.
High-Throughput Analytics
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 moreover 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 in chemically 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 the major challenges of 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 the 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.
Development of Smart Nanoparticle-Aptamer Sensing Technology
Quantum dots (QDs) are excellent donors in Förster resonance energy transfer (FRET)-based sensors because of their broad absorption and narrow symmetric emission. However, the strict requirement of a short donor—acceptor distance to achieve high FRET (hence sensitivity) has posed a significant challenge for QD-FRET-based sensors because of challenges associated with the preparation of QD conjugates that are both compact and highly stable. Consequently, most robust QD-FRET sensors are often too bulky to produce FRET efficiently, especially at low target-to-QD copy numbers. They have largely relied on increasing the target: QD ratio to achieve high FRET, making them undesirable and inefficient in situations of low target: QD copy numbers.
Herein the authors report their work on the preparation of stable, compact, and water-soluble QDs and their subsequent use in making compact, functional QD-DNA-based smart nanoparticle sensors for labeled and label-free DNA and protein detection. The authors, Zhang et al. developed two strategies to prepare QD-DNA sensors: (1) via QD-thiolated DNA self-assembly, and (2) via covalent coupling between DNA and a QD surface ligand functional group. The authors found that thiolated DNA (fluorophore labeled) can self-assemble onto a three-mercaptopropionic acid-capped QDs to produce highly efficient FRET (∼80%) at a DNA:QD ratio of 1:1. This system, however, suffers from strong nonspecific adsorption and the self-assembled single-stranded (ss) DNA target is unable to hybridize to its complementary probe.
More recently, the authors find that a dihydrolipoic acid-capped QD-ssDNA self-assembled system can hybridize to a labeled complementary probe to produce efficient FRET that can be exploited for labeled DNA probe quantification. Further, incorporating an antithrombin DNA aptamer to this system leads to a QD-DNA aptamer sensor that can specifically detect a 10-nM unlabeled protein probe (thrombin). The nonspecific adsorption problem can be eliminated by introducing a poly(ethylene glycol) linker to the QD capping ligands or by capping the QD with a chelating dendritic ligand. The resulting QD-DNA sensors can specifically detect 1-nM unlabeled or 35-pM labeled DNA probes using QD-sensitized dye FRET signals on a conventional fluorimeter. Extension of the DNA target to other functional DNAs or DNA/RNA aptamers should allow the development of a multifunctional QD-DNA platform suitable for biosensing, disease diagnosis and therapeutic applications (Zhang, H. et al. Faraday Discuss
Protein Profiling for Cancer Biomarker Discovery Using Matrix-Assisted Laser Desorption/lonization Time-of-Flight Mass Spectrometry and Infrared Imaging: A Review
Biomarker discovery has been of utmost importance for several diseases. Numerous technologies with different underlying principles have been reported in literature. R. Bakry et al. from the Institute of Analytical Chemistry and Radio-chemistry of Austria, discuss the proteomic technologies for cancer biomarkers. The authors further focus on combining the features of the technologies to improve resolution. Cancer biomarker refers to a substance or process that is indicative of the presence of cancer in the body. A biomarker might be either a molecule secreted by a tumor or it can be a specific response of the body to the presence of cancer. Cancer biomarker-based diagnostics have applications for establishing disease predisposition, early detection, cancer staging, therapy selection, identifying whether or not a cancer is metastatic, therapy monitoring, assessing prognosis, and advances in the adjuvant setting. Full adoption of cancer biomarkers in the clinic has to date been slow, and only a limited number of cancer biomarker products are currently in routine use.
Among proteomic technologies, matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF/MS) is a technique that has allowed rapid progress in cancer biology. Different further developed methods including surface-enhanced laser desorption/ionization and material-enhanced laser desorption/ionization are simple and high-throughput techniques that analyze with high sensitivity and specificity intact proteins expressed in complex biological mixtures, such as serum, urine, and tissues. The combination of MS with infrared (IR) spectroscopic imaging is an attempt to combine different technologies in systems analytics. Both MALDI-TOF and IR tissue imaging enable studying proteins distribution in tissue samples with a resolution down to 50 and 5 μm, respectively. In this review, the authors summarize recent applications and the synergistic combination of these new technologies to proteomic profiling for cancer biomarker discovery (Bakry, R. et al. Anal. Chim. Acta. 2011, 690(1), 26-34).
Automation Systems
Enzyme-Based Assays in a Sequential Injection Format: A Review
Sequential injection analysis systems have been extensively exploited in the last decades for the implementation of enzyme-based assays aiming at the evaluation of enzyme activity or the determination of specific analytes. The most prominent aspects of the automation of enzymatic assays in these systems are discussed in this review. Special attention is devoted to the mode of enzyme manipulation in homogeneous or heterogeneous media and to the comparison with batch and flow injection enzyme methodologies. The possibility of implementing strategies for the enhancement of selectivity in specific determinations is also addressed. The more recent trends in this field are discussed focusing mainly on the miniaturization resorting to the lab-on valve platform and on the bead injection concept (Silvestre, C. I. et al. Anal. Chim. Acta. 2011, 689(2), 160-177).
Advances in Assay Development
From Tumor Immunology to Cancer Immunotherapy: Miles to Go
Advances in tumor immunology are supporting the clinical implementation of several immunological approaches to cancer in the clinical setting. However, the alternate success of current immunotherapeutic regimens underscores the fact that the molecular mechanisms underlying immune-mediated tumor rejection are still poorly understood. Given the complexity of the immune system network and the multidimensionality of tumor/host interactions, the comprehension of tumor immunology might greatly benefit from high-throughput microarray analysis, which can portrait the molecular kinetics of immune response on a genome-wide scale, thus accelerating the discovery pace and ultimately catalyzing the development of new hypotheses in cell biology. Although the general principles of microarray-based gene profiling with the application of DNA microarray have rapidly spread in the scientific community, the need for mastering this technique toproduce meaningful data and correctly interpret the enormous output of information generated by this technology is critical and represents a tremendous challenge for investigators. To describe the sequence of events conductive to an effective immune recognition and killing of malignant cells, clinicians might use gene profiling as a powerful tool to assess the activation status of the immune system before and during immunotherapy (Tiwari, M. J. Cancer Res. Ther. 2010, 6(4), 427-431).
Analysis of Multiple Compound-Protein Interactions Reveals Novel Bioactive Molecules
The discovery of novel bioactive molecules advances our systems-level understanding of biological processes and is crucial for innovation in drug development. For this purpose, the emerging field of chemical genomics is currently focused on accumulating large assay data sets describing compound-protein interactions (CPIs). Although new target proteins for known drugs have recently been identified through mining of CPI databases, using these resources to identify novel ligands remains unexplored. Here, H. Yabuuchi demonstrates that machine learning of multiple CPIs cannot only assess drug polypharmacology but can also efficiently identify novel bioactive scaffold-hopping compounds. Through a machine-learning technique that uses multiple CPIs, the author successfully identifies novel lead compounds for two pharmaceutically important protein families, G-protein-coupled receptors and protein kinases. These novel compounds are not identified by existing computational ligand-screening methods in comparative studies. The results of this study indicate that data derived from chemical genomics can be highly useful for exploring chemical space, and this systems biology perspective could accelerate drug discovery processes (Yabuuchi, H. Mol. Syst. Biol. 2011, 7, 472).
Footnotes