Advances in endometrial cancer protein biomarkers for use in the clinic

Introduction: Endometrial cancer (EC) is the fourth most common cancer in women in developed countries. The identification of sensitive and specific biomarkers to improve early detection of EC is crucial for an appropriate management of this disease, in which 30% of patients are diagnosed only at advanced stages, which is associated with high levels of morbidity and mortality. Despite major efforts and investments made to identify EC biomarkers, no protein has yet reached the stage of clinical application.

Areas covered: This review gathers the numerous candidate biomarkers for EC diagnosis proposed in proteomic studies published from 1978 to 2017. Additionally, we summarize limitations associated with the proteomic technologies and study designs employed in those articles. Finally, we address new perspectives in EC biomarker research, including the comprehensive knowledge of previously suggested candidate biomarkers in conjunction with novel mass spectrometry-based proteomic technologies with enhanced sensitivity and specificity not yet applied to EC studies and a directed clinical perspective in the study design.

Expert commentary: These ingredients could be the recipe to accelerate the application of protein biomarkers in the clinic.     

HomBlocks: A multiple-alignment construction pipeline for organelle phylogenomics based on locally collinear block searching

Organelle phylogenomic analysis requires precisely constructed multi-gene alignment matrices concatenated by pre-aligned single gene datasets. For non-bioinformaticians, it can take days to weeks to manually create high-quality multi-gene alignments comprising tens or hundreds of homologous genes. Here, we describe a new and highly efficient pipeline, HomBlocks, which uses a homologous block searching method to construct multiple sequence alignment. This approach can automatically recognize locally collinear blocks among organelle genomes and excavate phylogenetically informative regions to construct multiple sequence alignment in a few hours. In addition, HomBlocks supports organelle genomes without annotation and makes adjustment to different taxon datasets, thereby enabling the inclusion of as many common genes as possible. Topology comparison of trees built by conventional multi-gene and HomBlocks alignments implemented in different taxon categories shows that the same efficiency can be achieved by HomBlocks as when using the traditional method. The availability of Homblocks makes organelle phylogenetic analyses more accessible to non-bioinformaticians, thereby promising to lead to a better understanding of phylogenic relationships at an organelle genome level.

Automated hydrodynamic modelling of a complex between a human IgE fragment (FcÂ3–4) and the IgE high affinity receptor FcÂRI ⋅-chain

The binding of IgE to its high affinity receptor FcεRI plays an important role in the allergic response. The interaction between soluble FcεRIα-chain (sFcεRIα) and Fcε3–4, a fragment of IgE consisting of the Cε3 and Cε4 heavy chain constant domains, has been studied using analytical ultracentrifugation (Keown et al. this volume). Here we describe the development of a simple automated hydrodynamic modelling technique and its application to this interaction. This procedure utilises sphere models of the two molecules and performs an automated systematic translational search of sFcεRIα relative to Fcε3–4. The result of this is the generation of 40,359 individual models of how the receptor can be placed relative to Fcε3–4. These are then assessed for consistency by comparing the sedimentation coefficients generated for the models to the experimentally determined sedimentation coefficients, and are displayed graphically to show allowed and disallowed complexes. From this analysis, it is clear that the complex between sFcεRIα and Fcε3–4 is compact, with the most elongated models being excluded. In addition, sFcεRIα appears not to interact with the C-terminal end of Fcε3–4, and probably binds either to the sides or face, observations which are consistent with other experimental data on the FcεRIα/IgE interaction. Automated hydrodynamic modelling also has the potential to be used for other interactions, providing a simple way of looking at a large number of models, and making rigorous studies of interacting components more feasible. Received: 31 July 1996 / Accepted: 1 December 1996     

Manually and automatically produced pellet cultures of human primary chondrocytes: A comparative analysis

Cartilage defects are often associated with restriction of the locomotor system. New methods are required to investigate cartilage tissue and for the repair of cartilage tissue. 3D cultures are promising due to better simulation of in vivo conditions. The aim of this study was to provide a model system for studying cartilage tissue. We solved this problem by automated production of pellet cultures of human primary chondrocytes in media with and without antibiotics using the Biomek® Cell Workstation and consequent automated bioscreening with a high‐throughput screening system, and compared with the regular manual processes. The Biomek® Cell Workstation allows the cultivation of different cell types (suspensions cells and adherent cells) and 3D cell cultures (pellet cultures, alginate beads and spheroid cultures). The proliferation was analyzed by DNA quantification and compared with the EZ4U proliferation assay as a new tool for pellet cultures. The toxicity was evaluated by the detection of ubiquitous adenylate kinases. The proliferation increased from day 14 until day 35 and was associated with a decrease in the cytotoxicity. The comparative analysis showed similar results for manual and automated processes. We concluded that the manual methods can be replaced by automated processes (pellet manufacturing and screening), which would allow large‐scale procedures to support studies on cartilage regeneration.     

DNA sequencing research group: 2006 general survey of DNA sequencing facilities.

Over the past few years, technological advances in automated DNA sequencing have had a profound effect on the nature of DNA sequencing laboratories. To characterize the changes occurring within DNA sequencing facilities, the DNA Sequencing Research Group conducted three previous studies, in 1998, 2000, and 2003. A new general survey has been designed and conducted by the DSRG to capture the current status of DNA sequencing facilities in all sectors. Included were questions regarding facility administration, pricing, instrumentation, technology, protocols, and operation. The results of the survey are presented here, accompanied by comparisons to the previous surveys. These comparisons formed a basis for the discussion of trends within the facilities in response to the dynamics of a changing technology.     

Role of <Emphasis Type="Italic">Serratia marcescens</Emphasis> ACE2 on diesel degradation and its influence on corrosion

A facultative anaerobic species Serratia marcescens ACE2 isolated from the corrosion products of diesel transporting pipeline in North West, India was identified by 16S rDNA sequence analysis. The role of Serratia marcesens ACE2 on biodegradation of diesel and its influence on the corrosion of API 5LX steel has been elucidated. The degrading strain ACE2 is involved in the process of corrosion of steel API 5LX and also utilizes the diesel as an organic source. The quantitative biodegradation efficiency (BE) of diesel was 58%, calculated by gas-chromatography–mass spectrum analysis. On the basis of gas-chromatography–mass spectrum (GC–MS), Fourier Transform infrared spectroscopy (FTIR) and X-ray diffractometer (XRD), the involvement of Serratia marcescens on degradation and corrosion has been investigated. This basic study will be useful for the development of new approaches for detection, monitoring and control of microbial corrosion.     

Transient gene expression in CHO cells monitored with automated flow cytometry

Transient gene expression is frequently used in industry to rapidly generate usable quantities of a protein from cultured cells. In gene therapy applications it is used to express a therapeutic protein in vivo. A quantitative assessment of the expression kinetics is important because it enables optimization and control of culture conditions for higher productivity. Previous experimental studies show a characteristic peak in average protein expression per cell after transfection followed by an exponential decrease of the expressed protein. Here, we show that the exponential decrease in single cell expression of enhanced Green Fluorescent Protein (eGfp) occurs in discrete steps. We attribute this to the absence of plasmid replication and to symmetric partitioning of plasmid and eGfp between dividing cells. This is reflected in the total eGfp in the bioreactor, which increased at a constant rate throughout the experiment. Additionally, the data provide a detailed time course of cell physiology during recovery from electroporation. The time course of cell physiology precisely indicates when the culture shifts growth phases. Furthermore, the data indicate two unique stationary phases. One type of stationary phase occurs when proliferation ceases while cells decrease their cell size, maintain granularity, and mean eGfp content decreases. The second type occurs when proliferation ceases while cells increase their cell size, increase granularity, and surprisingly maintain eGfp content. The collected data demonstrate the utility of automated flow cytometry for unique bioreactor monitoring and control capabilities in accordance with the US Food and Drug Administration’s Process Analytical Technology initiative.     

Widely Targeted Metabolomics Based on Large-Scale MS/MS Data for Elucidating Metabolite Accumulation Patterns in Plants

Metabolomics is an ‘omics’ approach that aims toanalyze all metabolites in a biological sample comprehensively.The detailed metabolite profiling of thousands of plant sampleshas great potential for directly elucidating plant metabolicprocesses. However, both a comprehensive analysis and a highthroughput are difficult to achieve at the same time due tothe wide diversity of metabolites in plants. Here, we have establisheda novel and practical metabolomics methodology for quantifyinghundreds of targeted metabolites in a high-throughput manner.Multiple reaction monitoring (MRM) using tandem quadrupole massspectrometry (TQMS), which monitors both the specific precursorions and product ions of each metabolite, is a standard techniquein targeted metabolomics, as it enables high sensitivity, reproducibilityand a broad dynamic range. In this study, we optimized the MRMconditions for specific compounds by performing automated flowinjection analyses with TQMS. Based on a total of 61,920 spectrafor 860 authentic compounds, the MRM conditions of 497 compoundswere successfully optimized. These were applied to high-throughputautomated analysis of biological samples using TQMS coupledwith ultra performance liquid chromatography (UPLC). By thisanalysis, approximately 100 metabolites were quantified in eachof 14 plant accessions from Brassicaceae, Gramineae and Fabaceae.A hierarchical cluster analysis based on the metabolite accumulationpatterns clearly showed differences among the plant families,and family-specific metabolites could be predicted using a batch-learningself-organizing map analysis. Thus, the automated widely targetedmetabolomics approach established here should pave the way forlarge-scale metabolite profiling and comparative metabolomics.     

Automated structure determination from NMR spectra

Automated methods for protein structure determination by NMR have increasingly gained acceptance and are now widely used for the automated assignment of distance restraints and the calculation of three-dimensional structures. This review gives an overview of the techniques for automated protein structure analysis by NMR, including both NOE-based approaches and methods relying on other experimental data such as residual dipolar couplings and chemical shifts, and presents the FLYA algorithm for the fully automated NMR structure determination of proteins that is suitable to substitute all manual spectra analysis and thus overcomes a major efficiency limitation of the NMR method for protein structure determination.     

Virtual screening pipeline and ligand modelling for H5N1 neuraminidase

The H5N1 virus neuraminidase structure was solved in two different conformations depending on the inhibitor concentration. In the absence of oseltamivir or at a low concentration, the neuraminidase structure assumes an open form that closes at a high oseltamivir concentration due to the shift of the so-called 150-loop near the active site. Although the close conformation is similar to all the other structurally known neuraminidase types, it doesn’t appear to be the most likely physiological condition for N1.To investigate the specific ligand binding properties of the open form, we screened by docking simulation, a large dataset of ligands and compared the results with closed form. The virtual screening procedure was implemented in a docking pipeline that also performs a step-by-step, target specific, filtering approach for data reduction. The selected ligands display binding ability involving multiple sites of interaction including the active site and an adjacent cavity made available by the 150-loop shift. Two ligands are especially interesting and are proposed as substituents to design oseltamivir derivatives specifically suited for the open conformation.