Turning quantity into quality: novel quality assurance strategies for data produced by high-throughput genomics technologies

The pharmaceutical industry is facing the challenge of managing the exponential increase in volume, diversity and complexity of data generated by high-throughput technologies such as genome sequencing, gene-expression profiling, protein-expression profiling, metabolic profiling and high-throughput screening. These novel ‘genomics’ technologies are expected to reshape the approach of life science companies to research. Unfortunately, in many cases genomics technologies have been used uncritically, and some preliminary results have been disappointing. The lack of standardized data validation and quality assurance processes is recognized as one of the major hurdles for successfully implementing genomics technologies. This is particularly important for industrialized drug discovery processes, because more and more key conclusions and far-reaching decisions in the pharmaceutical industry are based on data that is generated automatically. Therefore, automated, specialized quality-control systems that can spot erroneous data that might obscure important biological effects are needed urgently. In this article, special emphasis is placed on DNA microarray technologies, a key genomics technology that suffers from severe problems with data quality. A generic, automatable data-quality-assurance workflow is discussed that will ultimately improve the quality of the drug candidates and, at the same time, reduce overall drug-development costs.     

Chemical-genomic profiling: systematic analysis of the cellular targets of bioactive molecules

Chemical-genomic (CG) profiling of bioactive compounds is a powerful approach for drug target identification and mode of action studies. Within the last decade, research focused largely on the development and application of CG approaches in the model yeast Saccharomyces cerevisiae. The success of these methods has sparked interest in transitioning CG profiling to other biological systems to extend clinical and evolutionary relevance. Additionally, CG profiling has proven to enhance drug-synergy screens for developing combinatorial therapies. Herein, we briefly review CG profiling, focusing on emerging cross-species technologies and novel drug-synergy applications, as well as outlining needs within the field.     

Biomedical applications of protein chips

The development of microchips involving proteins has accelerated within the past few years. Although DNA chip technologies formed the precedent, many different strategies and technologies have been used because proteins are inherently a more complex type of molecule. This review covers the various biomedical applications of protein chips in diagnostics, drug screening and testing, disease monitoring, drug discovery (proteomics), and medical research. The proteomics and drug discovery section is further subdivided to cover drug discovery tools (on-chip separations, expression profiling, and antibody arrays), molecular interactions and signaling pathways, the identification of protein function, and the identification of novel therapeutic compounds. Although largely focused on protein chips, this review includes chips involving cells and tissues as a logical extension of the type of data that can be generated from these microchips.     

Metabolomics for phytomedicine research and drug development

Metabolomics, including both targeted and global metabolite profiling strategies, is fast becoming the approach of choice across a broad range of sciences including systems biology, drug discovery, molecular and cell biology, and other medical and agricultural sciences. New analytical and bioinformatics technologies and techniques are continually being created or optimized, significantly increasing the crossdisciplinary capabilities of this new biology. The metabolomes of medicinal plants are particularly a valuable natural resource for the evidence-based development of new phytotherapeutics and nutraceuticals. Comparative metabolomics platforms are evolving into novel technologies for monitoring disease development, drug metabolism, and chemical toxicology. An efficient multidisciplinary marriage of these emerging metabolomics techniques with agricultural biotechnology will greatly benefit both basic and applied medical research.     

Chemical kinomics: a powerful strategy for target deconvolution

Kinomics is an emerging and promising approach for deciphering kinomes. Chemical kinomics is a discipline of chemical genomics that is also referred to as "chemogenomics", which is derived from chemistry and biology. Chemical kinomics has become a powerful approach to decipher complicated phosphorylation-based cellular signaling networks with the aid of small molecules that modulate kinase functions. Moreover, chemical kinomics has played a pivotal role in the field of kinase drug discovery as it enables identification of new molecular targets of small molecule kinase modulators and/or exploitation of novel functions of known kinases and has also provided novel chemical entities as hit/lead compounds. In this short review, contemporary chemical kinomics technologies such as activity-based protein profiling, T7 kinasetagged phages, kinobeads, three-hybrid systems, fluorescenttagged kinase binding assays, and chemical genomic profiling are discussed along with a novel allosteric Bcr-Abl kinase inhibitor (GNF-2/GNF-5) as a successful application of chemical kinomics approaches.     

The current state of the art of quantitative phosphoproteomics and its applications to diabetes research

Protein phosphorylation is a fundamental regulatory mechanism in many cellular processes and aberrant perturbation of phosphorylation has been implicated in various human diseases. Kinases and their cognate inhibitors have been considered as hotspots for drug development. Therefore, the emerging tools, which enable a system-wide quantitative profiling of phosphoproteome, would offer a powerful impetus in unveiling novel signaling pathways, drug targets and/or biomarkers for diseases of interest. This review highlights recent advances in phosphoproteomics, the current state of the art of the technologies and the challenges and future perspectives of this research area. Finally, some exemplary applications of phosphoproteomics in diabetes research are underscored.     

Understanding the role of gut microbiome-host metabolic signal disruption in health and disease

There is growing awareness of the importance of the gut microbiome in health and disease, and recognition that the microbe to host metabolic signalling is crucial to understanding the mechanistic basis of their interaction. This opens new avenues of research for advancing knowledge on the aetiopathologic consequences of dysbiosis with potential for identifying novel microbially-related drug targets. Advances in both sequencing technologies and metabolic profiling platforms, coupled with mathematical integration approaches, herald a new era in characterizing the role of the microbiome in metabolic signalling within the host and have far reaching implications in promoting health in both the developed and developing world.     

Biological complexity and drug discovery: a practical systems biology approach

Drugs fail in clinical studies most often from lack of efficacy or unexpected toxicities. These failures result from an inadequate understanding of drug action and follow, in part, from our dependence on drug discovery technologies that do not take into account the complexity of human disease biology. Biological systems exhibit many features of complex engineering systems, including modularity, redundancy, robustness, and emergent properties. Addressing these features has contributed to the successful design of an improved biological assay technology for inflammation drug discovery. This approach, termed Biologically Multiplexed Activity Profiling (BioMAP), involves the statistical analysis of protein datasets generated from novel complex primary human cell-based assay systems. Compound profiling in these systems has revealed that a surprisingly large number of biological mechanisms can be detected and distinguished. Features of these assays relevant to the behaviour of complex systems are described.     

A consolidated approach to analyzing data from high-throughput protein microarrays with an application to immune response profiling in humans.

Motivation: DNA microarrays are a well-known and established technology in biological and pharmaceutical research providing a wealth of information essential for understanding biological processes and aiding drug development. Protein microarrays are quickly emerging as a follow-up technology, which will also begin to experience rapid growth as the challenges in protein to spot methodologies are overcome. Like DNA microarrays, their protein counterparts produce large amounts of data that must be suitably analyzed in order to yield meaningful information that should eventually lead to novel drug targets and biomarkers. Although the statistical management of DNA microarray data has been well described, there is no available report that offers a successful consolidated approach to the analysis of high-throughput protein microarray data. We describe the novel application of a statistical methodology to analyze the data from an immune response profiling assay using human protein microarray with over 5000 proteins on each chip.     

Antigen arrays for antibody profiling

Antigen array technologies enable large-scale profiling of the specificity of antibody responses against autoantigens, tumor antigens and microbial antigens. Antibody profiling will provide insights into pathogenesis, and will enable development of novel tests for diagnosis and guiding therapy in the clinic. Recent advances in the field include development of antigen array-based approaches to examine immune responses against antigens encoded in genetic libraries, post-translationally modified proteins, and other biomolecules such as lipids. A promising application is the use of antibody profiling to guide development and selection of antigen-specific therapies to treat autoimmune disease. This review discusses these advances and the challenges ahead for development and refinement of antibody profiling technologies for use in the research laboratory and the clinic.     

Profiling the global tyrosine phosphorylation state

Protein tyrosine kinases and protein tyrosine phosphatases play a key role in cell signaling, and the recent success of specific tyrosine kinase inhibitors in cancer treatment strongly validates the clinical relevance of basic research on tyrosine phosphorylation. Functional profiling of the tyrosine phosphoproteome is likely to lead to the identification of novel targets for drug discovery and provide a basis for novel molecular diagnostic approaches. The ultimate aim of current mass spectrometry-based phosphoproteomic approaches is the comprehensive characterization of the phosphoproteome. However, current methods are not yet sensitive enough for routine detection of a large percentage of tyrosine-phosphorylated proteins, which are generally of low abundance. In this article, we discuss alternative methods that exploit Src homology 2 (SH2) domains for profiling the tyrosine phosphoproteome. SH2 domains are small protein modules that bind specifically to tyrosine-phosphorylated peptides; there are more than 100 SH2 domains in the human genome, and different SH2 domains bind to different classes of tyrosine-phosphorylated ligands. These domains play a critical role in the propagation of signals in the cell, mediating the relocalization and complex formation of proteins in response to changes in tyrosine phosphorylation. We have developed an SH2 profiling method based on far-Western blotting, in which a battery of SH2 domains is used to probe the global state of tyrosine phosphorylation. Application to the classification of human malignancies suggests that this approach has potential as a molecular diagnostic tool. We also describe ongoing efforts to modify and improve SH2 profiling, including the development of a multiplexed assay system that will allow high-throughput functional profiling of the tyrosine phosphoproteome.     

A unique automation platform for measuring low level radioactivity in metabolite identification studies

Generation and interpretation of biotransformation data on drugs, i.e. identification of physiologically relevant metabolites, defining metabolic pathways and elucidation of metabolite structures, have become increasingly important to the drug development process. Profiling using (14)C or (3)H radiolabel is defined as the chromatographic separation and quantification of drug-related material in a given biological sample derived from an in vitro, preclinical in vivo or clinical study. Metabolite profiling is a very time intensive activity, particularly for preclinical in vivo or clinical studies which have defined limitations on radiation burden and exposure levels. A clear gap exists for certain studies which do not require specialized high volume automation technologies, yet these studies would still clearly benefit from automation. Use of radiolabeled compounds in preclinical and clinical ADME studies, specifically for metabolite profiling and identification are a very good example. The current lack of automation for measuring low level radioactivity in metabolite profiling requires substantial capacity, personal attention and resources from laboratory scientists. To help address these challenges and improve efficiency, we have innovated, developed and implemented a novel and flexible automation platform that integrates a robotic plate handling platform, HPLC or UPLC system, mass spectrometer and an automated fraction collector.     

Veterinary vaccines

Vaccination of animals for the prevention of infectious diseases has been practised for a number of years with little change in product composition. Recent advances in molecular biology, pathogenesis and immunology have laid the groundwork for the development of a new generation of veterinary vaccines based on pure subunits as well as live vectored bacteria and viruses. Along with novel methods of antigen preparation, the use of new adjuvants and delivery systems will permit targeting of the appropriate immune response as well as offering flexibility in terms of vaccination protocols. These new technologies are also being applied to the development of vaccines to enhance animal productivity and to control reproduction.     

Oxylipin analysis methods

Practical guidelines for monitoring and measuring compounds such as jasmonates, ketols, ketodi(tri)enes and hydroxy-fatty acids as well as detecting the presence of novel oxylipins are presented. Additionally, a protocol for the penetrant analysis of non-enzymatic lipid oxidation is described. Each of the methods, which employ gas chromatography/mass spectrometry, can be applied without specialist knowledge or recourse to the latest analytical instrumentation. Additional information on oxylipin quantification and novel protocols for preparing oxygen isotope-labelled internal standards are provided. Four developing areas of research are identified: (i) profiling of the unbound cellular pools of oxylipins; (ii) profiling of esterified oxylipins and/or monitoring of their release from parent lipids; (iii) monitoring of non-enzymatic lipid oxidation; (iv) analysis of unstable and reactive oxylipins. The methods and protocols presented herein are designed to give technical insights into the first three areas and to provide a platform from which to enter the fourth area.