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Studies on membrane proteins can help to develop new drug targets and treatments for a variety of diseases. However, membrane proteins continue to be among the most challenging targets in structural biology. This uphill endeavor can be even harder for membrane proteins from Mycobacterium species, which are notoriously difficult to express in heterologous systems. Arabino- furanosyltransferases are involved in mycobacterial cell wall synthesis and thus potential targets for antituberculosis drugs. A set of 96 mycobacterial genes coding for Arabinofuranosyltransferases was selected, of which 17 were successfully expressed in E. coli and purified by metal-affinity chro- matography. We herein present an efficient high-throughput strategy to screen in microplates a large number of targets from Mycobacteria and select the best conditions for large-scale protein production to pursue functional and structural studies. This methodology can be applied to other targets, is cost and time effective and can be implemented in common laboratories

The expression analysis of recombinant proteins is a challenging step in any high-throughput protein production pipeline. Often multiple expression systems and a variety of expression construct designs are considered for the production of a protein of interest. There is a strong need to triage constructs rapidly and systematically. This chapter describes a semiautomated method for the simultaneous purification and characterization of proteins expressed from multiple samples of expression cultures from the E. coli, baculovirus expression vector system, and mammalian transient expression systems. This method assists in the selection of the most promising expression construct(s) or the most favorable expression condition(s) to move forward into large-scale protein production.

Recently, volatile organic compounds (VOCs) in outdoor air pollution have led to major public health problems and the identification of specific minimally invasive biomarkers for assessing environmental toxicant exposure has become increasingly important. However, research into the human health effects of inhalation exposure to VOCs remains insufficient. Using a microarray based approach, we identified and validated characteristic mRNA expression profiles in the human whole blood of workers exposed to VOCs (toluene, ethylbenzene, and xylene), which were then compared with genomic level expressions in workers not exposed to the toxicants. We surveyed 141 workers working in a chemical production factory, of which 66 were not exposed to VOCs. We identified 4384 characteristic discernible exposure indicator mRNAs for toluene, 1296 for ethylbenzene, and 5821 for xylene. Using these, we were able to discern those subjects from the control group to a higher accuracy, sensitivity, and specificity than when using urinary biomarkers. The results showed that altered levels of mRNA can be a reliable, novel, and minimally invasive biological indicator of occupational exposure to VOCs. Future research directions should consider the adverse effects of exposure to VOCs on epigenetic regulation.

e16065 Background: The molecular pathogenesis of colon adenocarcinoma (COAD) is attributed to large molecular changes such as Chromosomal Instability and high somatic copy number variation or defective DNA mismatch repair and consequent microsatellite instability (MSI). The prevalence of this type of cancer is increasing in the state of Kerala, India. A detailed study of the signaling pathways could lead to a better understanding of the central molecular pathological changes and potential biomarkers particular to this population. Methods: High throughput somatic expression analysis using Nanostring PanCancer pathway panel assay was performed. Differentially expressed (DE) genes were selected and KEGG pathway enrichment analysis was performed for assessment of canonical signaling pathways. Expression profiles were compared against the public database, Colon Adenocarcinoma cohort of the Cancer Genome Atlas (TCGA-COAD), using the Genome Expression Profiling Interactive Analysis (GEPIA). Protein-protein interaction network analysis was done using Cytoscape. DE genes were compared against immune cell infiltration in the TCGA-COAD from Tumor Immune Estimation Resource (TIMER) databases. Results: Nanostring assay was performed in 10 Tumor-Normal paired FFPE samples of stage II/III colon adenocarcinoma. Out of > 700 genes, significant difference in expression was found in 83 genes (FDR adjusted p -value < 0.01) with fold-change |fc(log2)| of at least one. Fold-change |fc(log2)| ≥ 2 was found in 19/83 genes. Network analysis clustered 13 out of 17 upregulated genes. Superimposition of the current data on TCGA study showed that among the three genes, four (MET, MCM2, ETV4 and MMP7), were common. DE Genes which were not significant in TCGA COAD study such as INHBA, COL1A1, COL11A1, COMP, SFRP4, SPP1, IL11, LIF, WT1 and DDIT4, were found to be significant in the current study. A few of the unique genes identified in the current study were found to have significant correlation with antigen presenting cells infiltration in the TCGA-COAD studies. Conclusions: Many DE genes from the study population were found to be different from previous large cohort studies in other population. This may suggest a different pathogenesis of COAD in this population, warranting a detailed study on the pathogenesis.

Circular RNAs (circRNAs) were recently discovered as a class of widely expressed noncoding RNA and have been implicated in regulation of gene expression. However, the function of the majority of circRNAs remains unknown. Studies of circRNAs have been hampered by a lack of essential approaches for detection, quantification and visualization. We therefore developed a target-enrichment sequencing method suitable for high-throughput screening of circRNAs and their linear counterparts. We also applied padlock probes and in situ sequencing to visualize and determine circRNAs localization in human brain tissue at subcellular levels. We measured circRNA abundance across different human samples and tissues. Our results demonstrate the potential of this RNA class to act as a specific diagnostic marker in blood and serum, by detection of circRNAs from genes exclusively expressed in the brain. The powerful and scalable tools we present will enable studies of circRNA function and facilitate screening of circRNA as diagnostic biomarkers.

High-throughput (HT) methodologies have had a tremendous impact on structural biology of soluble proteins. High-resolution structure determination relies on the ability of the macromolecule to form ordered crystals that diffract X-rays. While crystallization remains somewhat empirical, for a given protein, success is proportional to the number of conditions screened and to the number of variants trialed. HT techniques have greatly increased the number of targets that can be trialed and the rate at which these can be produced. In terms of number of structures solved, membrane proteins appear to be lagging many years behind their soluble counterparts. Likewise, HT methodologies for production and characterization of these hydrophobic macromolecules are only now emerging. Presented here is an HT platform designed exclusively for membrane proteins that has processed over 5000 targets.

Summary The application of high throughput expression profiling and other advanced molecular biology laboratory techniques has revolutionised the management of cancers and is gaining attention in the field of gynaecological cancers. Such new approaches may help to improve our understanding of carcinogenesis and facilitate screening and early detection of gynaecological cancers and their precursors. Individualised prediction of patients’ responses to therapy and design of personalised molecular targeted therapy is also possible. The studies of various molecular targets involved in the various signal pathways related to carcinogenesis are particularly relevant to such applications. At the moment, the application of detection and genotyping of human papillomavirus in management of cervical cancer is one of the most well established appliances of molecular targets in gynaecological cancers. Methylation, telomerase and clonality studies are also potentially useful, especially in assisting diagnosis of difficult clinical scenarios. This postgenomic era of clinical medicine will continue to make a significant impact in routine pathology practice. The contribution of pathologists is indispensable in analysis involving tissue microarray. On the other hand, both pathologists and bedside clinicians should be aware of the limitation of these molecular targets. Interpretation must be integrated with clinical and histopathological context to avoid misleading judgement. The importance of quality assurance of all such molecular techniques and their ethical implications cannot be over-emphasised.

High throughput expression profiling and genotyping technologies provide the means to study the genetic determinants of population variation in gene expression variation. In this paper we present a general statistical framework for the simultaneous analysis of gene expression data and SNP genotype data measured for the same cohort. The framework consists of methods to associate transcripts with SNPs affecting their expression, algorithms to detect subsets of transcripts that share significantly many associations with a subset of SNPs, and methods to visualize the identified relations. We apply our framework to SNP-expression data collected from 50 breast cancer patients. Our results demonstrate an overabundance of transcript-SNP associations in this data, and pinpoint SNPs that are potential master regulators of transcription. We also identify several statistically significant transcript-subsets with common putative regulators that fall into well-defined functional categories.

The field of molecular genetics has blossomed into a multidisciplinary entity that is revolutionizing the way researchers evaluate a myriad of critical concepts such as development, homeostasis, and disease pathogenesis. There is tremendous interest in the quantitative assessment of tissue-specific expression of both newly identified noncoding RNAs and regulatory elements as well as identified genes and encoded proteins. High throughput expression profiling technologies have effectively altered the experimental design of gene expression assessments. Microarray platforms are still at the center of this paradigm shift, as they provide an affordable, simultaneous assessment of expression levels of a sample preparation in a single experiment and provide both hypothesis-driven and interrogative analyses.

ZHENG is the key theory in traditional Chinese medicine (TCM) and it is very important to find the molecular pharmacology of traditional Chinese herbal formulae. One ZHENG is related to many diseases and the herbal formulae are aiming to ZHENG. Therefore, many herbal formulae whose effects on a certain disease have been confirmed might also treat other diseases with the same ZHENG. In this study, the microarrays collected from patients with QiXuXueYu ZHENG (Qi-deficiency and Blood-stasis syndrome) before treatment and after being treated with Fuzheng Huayu Capsule were analyzed by a high-throughput gene microarrays-based drug similarity comparison method, which could find the small molecules which had similar effects with Fuzheng Huayu Capsule. Besides getting the results of anti-inflammatory and anti-fibrosis drugs which embody the known effect of Fuzheng Huayu Capsule, many other small molecules were screened out and could reflect other types of effects of this formula in treating QiXuXueYu ZHENG, including anti-hyperglycemic, anti-hyperlipidemic, hyposenstive effect. Then we integrated this information to display the effect of Fuzheng Huayu Capsule and its potential multiple-target molecular pharmacology. Moreover, through using clinical blood-tested data to verify our prediction, Fuzheng Huayu Capsule was proved to have effects on diabetes and dyslipidemia.

Most of the vaccines available today, albeit very effective, have been developed using traditional "old-style" methodologies. Technologies developed in recent years have opened up new perspectives in the field of vaccinology and novel strategies are now being used to design improved or new vaccines against infections for which preventive measures do not exist. The Reverse Vaccinology (RV) approach is one of the most powerful examples of biotechnology applied to the field of vaccinology for identifying new protein-based vaccines. RV combines the availability of genomic data, the analyzing capabilities of new bioinformatic tools, and the application of high throughput expression and purification systems combined with serological screening assays for a coordinated screening process of the entire genomic repertoire of bacterial, viral, or parasitic pathogens. The application of RV to Neisseria meningitidis serogroup B represents the first success of this novel approach. In this chapter, we describe how this revolutionary approach can be easily applied to any pathogen.

Introduction: Laser capture microdissection (LCM) facilitates procurement of defined cell populations for study in the context of histopathology. The morphologic assessment step in the LCM procedure is time consuming and tedious, thus restricting the utility of the technology for large applications. Results: Here, we describe the use of Spatially Invariant Vector Quantization (SIVQ) for histological analysis and LCM. Using SIVQ, we selected vectors as morphologic predicates that were representative of normal epithelial or cancer cells and then searched for phenotypically similar cells across entire tissue sections. The selected cells were subsequently auto-microdissected and the recovered RNA was analyzed by expression microarray. Gene expression profiles from SIVQ-LCM and standard LCM-derived samples demonstrated highly congruous signatures, confirming the equivalence of the differing microdissection methods. Conclusion: SIVQ-LCM improves the work-flow of microdissection in two significant ways. First, the process is transformative in that it shifts the pathologist′s role from technical execution of the entire microdissection to a limited-contact supervisory role, enabling large-scale extraction of tissue by expediting subsequent semi-autonomous identification of target cell populations. Second, this work-flow model provides an opportunity to systematically identify highly constrained cell populations and morphologically consistent regions within tissue sections. Integrating SIVQ with LCM in a single environment provides advanced capabilities for efficient and high-throughput histological-based molecular studies.

Integral membrane proteins are a major challenge within structural genomics. These proteins are not only difficult to produce in quantities sufficient for analysis by X-ray diffraction or NMR, but also require extraction from their lipid environment, which leads to a new dimension of difficulties in purification and subsequent structural analysis. To overcome these problems requires new strategies enabling screening larger number of parameters dealing with expression and purification. For this reason, we have developed high-throughput methods for screening extracting and purifying detergents as well as other purification parameters, e.g. salt and pH. The method requires standard laboratory equipments, but can also be automated.

The provision of high-quality protein in adequate quantities is a prerequisite for any structural genomics programme. A number of proteins from the Mycobacterium tuberculosis genome have been expressed and the success at each stage of the process assessed. Major difficulties have been encountered in the purification and solubilization of many of these proteins, most likely as a result of mis-folding. Some improvements have been made to the protocol but the overall success rate is still limited; however, the use of a cell-free protein expression system will circumvent some of the difficulties encountered. Alternative purification systems are also required and the properties of a mutant blue copper protein are described, that may offer a combined purification and tagging system.

By using automation and affinity-tag technologies, analysis of the large number of ORFs generated by genome-sequencing projects is greatly accelerated. Protocols describing culture of E. coli in automation-compatible formats and subsequent micro-to large-scale automated purification of 6xHis-tagged proteins are presented.

High-throughput protein structure analysis of individual protein domains requires analysis of large numbers of expression clones to identify suitable constructs for structure determination. For this purpose, methods need to be implemented for fast and reliable screening of the expressed proteins as early as possible in the overall process from cloning to structure determination.

cDNA expression microarrays are becoming popular tools for high throughput expression profiling. To simplify use of the microarrays in research lab, we developed a disposable plastic chamber, which can be used for a hybridization assay with a single slide. We compare performance of the hybridization assay using conventional glass slide-cover slide with 50 µl of hybridization mix and hybridization chamber with 1 ml of hybridization solution. We have developed a procedure for generating highly sensitive fluorescently labeled cDNA probes. Low complexity hybridization probes were generated from poly(A)+RNA using mixture of gene-specific primers. Using allylamino-modified dUTP allows one to generate the cDNA containing primary amino groups, which can be efficiently coupled with Cy3 or Cy5 succinimid ester. Under the optimal hybridization buffer composition, both approaches give similar sensitivity. The hybridization chamber approach does not require any specialized equipment and can be used in any research lab.