From Workstations to Workbenches: Towards Predicting Physicochemically Viable Protein-Protein Interactions Across a Host and a Pathogen

The understanding of protein-protein interactions is indispensable in comprehending most of the biological processes in a cell. Small-scale experiments as well as large-scale high-throughput techniques over the past few decades have facilitated identification and analysis of protein-protein interactions which form the basis of much of our knowledge on functional and regulatory aspects of proteins. However, such rich catalog of interaction data should be used with caution when establishing protein-protein interactions in silico, as the high-throughput datasets are prone to false positives. Numerous computational means developed to pursue genome-wide studies on protein-protein interactions at times overlook the mechanistic and molecular details, thus questioning the reliability of predicted protein-protein interactions. We review the development, advantages, and shortcomings of varied approaches and demonstrate that by providing a structural viewpoint in terms of shape complementarity and interaction energies at protein-protein interfaces coupled with information on expression and localization of proteins homologous to an interacting pair, it is possible to assess the credibility of predicted interactions in biological context. With a focus on human pathogen Mycobacterium tuberculosis H37Rv, we show that such scrupulous use of details at the molecular level can predict physicochemically viable protein-protein interactions across host and pathogen. Such predicted interactions have the potential to provide molecular basis of probable mechanisms of pathogenesis and hence open up ways to explore their usefulness as targets in the light of drug discovery. (c) 2014 IUBMB Life, 66(11):759-774, 2014

Exploring the Crystal Structure Landscape with a Heterosynthon Module: Fluorobenzoic Acid:1,2-Bis(4-pyridyl)ethylene 2:1 Cocrystals

The crystal structure landscape of the 2:1 benzoic acid:dipyridylethylene cocrystal (BA:DPE-I) is explored experimentally with fluoro-substituted benzoic acids and extended with studies employing the Cambridge Structural Database (CSD). The interpretation of the cocrystal landscape is facilitated by considering the kinetically favored and robust acidpyridine heterosynthon as a modular unit. Information based on high-throughput crystallography shows that polymorphs and pseudopolymorphs may belong to the same landscape but arise from different crystallization pathways because of complex and different kinetic features, and secondary synthon preferences. Using the CSD as a guide, the coformer was changed from 1,2-bis(4-pyridyl)ethylene (DPE-I) to 1,2-bis(4-pyridyl)ethane (DPE-II) and this provides an extended interpretation of the BA:DPE-I cocrystal landscape, also highlighting the complexity of the kineticthermodynamic dichotomy during the molecule-to-crystal progression.

IR spectroscopy as a probe for C-H center dot center dot center dot X hydrogen bonded supramolecular synthons

Weak hydrogen bonds of the type C-H center dot center dot center dot X (X: N, O, S and halogens) have evoked considerable interest over the years, especially in the context of crystal engineering. However, association patterns of weak hydrogen bonds are generally difficult to characterize, and yet the identification of such patterns is of interest, especially in high throughput work or where single crystal X-ray analysis is difficult or impossible. To obtain structural information on such assemblies, we describe here a five step IR spectroscopic method that identifies supramolecular synthons in weak hydrogen bonded dimer assemblies, bifurcated systems, and p-electron mediated synthons. The synthons studied here contain C-H groups as hydrogen bond donors. The method involves: (i) identifying simple compounds/cocrystals/salts that contain the hydrogen bonded dimer synthon of interest or linear hydrogen bonded assemblies between the same functionalities; (ii) scanning infrared (IR) spectra of the compounds; (iii) identifying characteristic spectral differences between dimer and linear; (iv) assigning identified bands as marker bands for identification of the supramolecular synthon, and finally (v) identifying synthons in compounds whose crystal structures are not known. The method has been effectively implemented for assemblies involving dimer/linear weak hydrogen bonds in nitrobenzenes (C-H center dot center dot center dot O-NO), nitro-dimethylamino compounds (NMe2 center dot center dot center dot O2N), chalcones (C-H center dot center dot center dot O=C), benzonitriles (C-H center dot center dot center dot N C) and fluorobenzoic acids (C-H center dot center dot center dot F-C). Two other special cases of C-H center dot center dot center dot pi and N-H center dot center dot center dot pi synthons were studied in which the band shape of the C-H stretch in hydrocarbons and the N-H deformation in aminobenzenes was examined.

Status of the crystallography beamlines at Elettra

Elettra is one of the first 3rd-generation storage rings, recently upgraded to routinely operate in top-up mode at both 2.0 and 2.4 GeV. The facility hosts four dedicated beamlines for crystallography, two open to the users and two under construction, and expected to be ready for public use in 2015. In service since 1994, XRD1 is a general-purpose diffraction beamline. The light source for this wide (4-21 keV) energy range beamline is a permanent magnet wiggler. XRD1 covers experiments ranging from grazing incidence X-ray diffraction to macromolecular crystallography, from industrial applications of powder diffraction to X-ray phasing with long wavelengths. The bending magnet powder diffraction beamline MCX has been open to users since 2009, with a focus on microstructural investigations and studies under non-ambient conditions. A superconducting wiggler delivers a high photon flux to a new fully automated beamline dedicated to macromolecular crystallography and to a branch beamline hosting a high-pressure powder X-ray diffraction station (both currently under construction). Users of the latter experimental station will have access to a specialized sample preparation laboratory, shared with the SISSI infrared beamline. A high throughput crystallization platform equipped with an imaging system for the remote viewing, evaluation and scoring of the macromolecular crystallization experiments has also been established and is open to the user community.

Molecular dynamics insight to phase transition in n-alkanes with carbon nanofillers

The present work aims to investigate the phase transition, dispersion and diffusion behavior of nanocomposites of carbon nanotube (CNT) and straight chain alkanes. These materials are potential candidates for organic phase change materials(PCMs) and have attracted flurry of research recently. Accurate experimental evaluation of the mass, thermal and transport properties of such composites is both difficult as well as economically taxing. Additionally it is crucial to understand the factors that results in modification or enhancement of their characteristic at atomic or molecular level. Classical molecular dynamics approach has been extended to elucidate the same. Bulk atomistic models have been generated and subjected to rigorous multistage equilibration. To reaffirm the approach, both canonical and constant-temperature, constant-pressure ensembles were employed to simulate the models under consideration. Explicit determination of kinetic, potential, non-bond and total energy assisted in understanding the enhanced thermal and transport property of the nanocomposites from molecular point of view. Crucial parameters including mean square displacement and simulated self diffusion coefficient precisely define the balance of the thermodynamic and hydrodynamic interactions. Radial distribution function also reflected the density variation, strength and mobility of the nanocomposites. It is expected that CNT functionalization could improve the dispersion within n-alkane matrix. This would further ameliorate the mass and thermal properties of the composite. Additionally, the determined density was in good agreement with experimental data. Thus, molecular dynamics can be utilized as a high throughput technique for theoretical investigation of nanocomposites PCMs. (C) 2015 Author(s). All article content, except where otherwise noted, is licensed under a Creative Commons Attribution 3.0 Unported License.

Field-Portable Microfluidics-Based Imaging Flow Cytometer

Clinical microscopy is a versatile and robust tool used for the diagnosis of a plethora of diseases. However, due to various reasons, it remains inaccessible in resource limited settings. In this paper, we present an automated and cost-effective alternative to microscopy for use in clinical diagnostics. With the use of custom optics and microfluidics, we demonstrate a field-portable imaging flow cytometry system. Using the presented system, we have been able to image 586 cells per second. We demonstrate the clinical relevance of the proposed system by differentiating between suspensions of healthy and sphered RBCs based on high-throughput morphometric analysis. The instrument presented here is a major advancement in the domain of field portable diagnostics as it enables fast and robust quantitative diagnostic testing at the point-of-care.

Evolution of bacterial transcription factors: how proteins take on new tasks, but do not always stop doing the old ones

Many bacterial transcription factors do not behave as per the textbook operon model. We draw on whole genome work, as well as reported diversity across different bacteria, to argue that transcription factors may have evolved from nucleoid-associated proteins. This view would explain a large amount of recent data gleaned from high-throughput sequencing and bioinformatic analyses.

Simultaneous acquisition of three NMR spectra in a single experiment for rapid resonance assignments in metabolomics

NMR-based approach to metabolomics typically involves the collection of two-dimensional (2D) heteronuclear correlation spectra for identification and assignment of metabolites. In case of spectral overlap, a 3D spectrum becomes necessary, which is hampered by slow data acquisition for achieving sufficient resolution. We describe here a method to simultaneously acquire three spectra (one 3D and two 2D) in a single data set, which is based on a combination of different fast data acquisition techniques such as G-matrix Fourier transform (GFT) NMR spectroscopy, parallel data acquisition and non-uniform sampling. The following spectra are acquired simultaneously: (1) C-13 multiplicity edited GFT (3,2)D HSQC-TOCSY, (2) 2D H-1- H-1] TOCSY and (3) 2D C-13- H-1] HETCOR. The spectra are obtained at high resolution and provide high-dimensional spectral information for resolving ambiguities. While the GFT spectrum has been shown previously to provide good resolution, the editing of spin systems based on their CH multiplicities further resolves the ambiguities for resonance assignments. The experiment is demonstrated on a mixture of 21 metabolites commonly observed in metabolomics. The spectra were acquired at natural abundance of C-13. This is the first application of a combination of three fast NMR methods for small molecules and opens up new avenues for high-throughput approaches for NMR-based metabolomics.

Framework for morphometric classification of cells in imaging flow cytometry

Imaging flow cytometry is an emerging technology that combines the statistical power of flow cytometry with spatial and quantitative morphology of digital microscopy. It allows high-throughput imaging of cells with good spatial resolution, while they are in flow. This paper proposes a general framework for the processing/classification of cells imaged using imaging flow cytometer. Each cell is localized by finding an accurate cell contour. Then, features reflecting cell size, circularity and complexity are extracted for the classification using SVM. Unlike the conventional iterative, semi-automatic segmentation algorithms such as active contour, we propose a noniterative, fully automatic graph-based cell localization. In order to evaluate the performance of the proposed framework, we have successfully classified unstained label-free leukaemia cell-lines MOLT, K562 and HL60 from video streams captured using custom fabricated cost-effective microfluidics-based imaging flow cytometer. The proposed system is a significant development in the direction of building a cost-effective cell analysis platform that would facilitate affordable mass screening camps looking cellular morphology for disease diagnosis. Lay description In this article, we propose a novel framework for processing the raw data generated using microfluidics based imaging flow cytometers. Microfluidics microscopy or microfluidics based imaging flow cytometry (mIFC) is a recent microscopy paradigm, that combines the statistical power of flow cytometry with spatial and quantitative morphology of digital microscopy, which allows us imaging cells while they are in flow. In comparison to the conventional slide-based imaging systems, mIFC is a nascent technology enabling high throughput imaging of cells and is yet to take the form of a clinical diagnostic tool. The proposed framework process the raw data generated by the mIFC systems. The framework incorporates several steps: beginning from pre-processing of the raw video frames to enhance the contents of the cell, localising the cell by a novel, fully automatic, non-iterative graph based algorithm, extraction of different quantitative morphological parameters and subsequent classification of cells. In order to evaluate the performance of the proposed framework, we have successfully classified unstained label-free leukaemia cell-lines MOLT, K562 and HL60 from video streams captured using cost-effective microfluidics based imaging flow cytometer. The cell lines of HL60, K562 and MOLT were obtained from ATCC (American Type Culture Collection) and are separately cultured in the lab. Thus, each culture contains cells from its own category alone and thereby provides the ground truth. Each cell is localised by finding a closed cell contour by defining a directed, weighted graph from the Canny edge images of the cell such that the closed contour lies along the shortest weighted path surrounding the centroid of the cell from a starting point on a good curve segment to an immediate endpoint. Once the cell is localised, morphological features reflecting size, shape and complexity of the cells are extracted and used to develop a support vector machine based classification system. We could classify the cell-lines with good accuracy and the results were quite consistent across different cross validation experiments. We hope that imaging flow cytometers equipped with the proposed framework for image processing would enable cost-effective, automated and reliable disease screening in over-loaded facilities, which cannot afford to hire skilled personnel in large numbers. Such platforms would potentially facilitate screening camps in low income group countries; thereby transforming the current health care paradigms by enabling rapid, automated diagnosis for diseases like cancer.

Quantitative RNA-seq analysis of the campylobacter jejuni transcriptome

Campylobacter jejuni is the most common bacterial cause of foodborne disease in the developed world. Its general physiology and biochemistry, as well as the mechanisms enabling it to colonize and cause disease in various hosts, are not well understood, and new approaches are required to understand its basic biology. High-throughput sequencing technologies provide unprecedented opportunities for functional genomic research. Recent studies have shown that direct Illumina sequencing of cDNA (RNA-seq) is a useful technique for the quantitative and qualitative examination of transcriptomes. In this study we report RNA-seq analyses of the transcriptomes of C. jejuni (NCTC11168) and its rpoN mutant. This has allowed the identification of hitherto unknown transcriptional units, and further defines the regulon that is dependent on rpoN for expression. The analysis of the NCTC11168 transcriptome was supplemented by additional proteomic analysis using liquid chromatography-MS. The transcriptomic and proteomic datasets represent an important resource for the Campylobacter research community. © 2011 SGM.

Development Of Biosensor Based On Imaging Ellipsometry

The concept of biosensor based on imaging ellipsometry was proposed ten years ago. Its principle and the methodology as well as some solutions to problems which have to be faced during the development are mentioned. Its properties of phase sensitive, high throughput and fast sampling, as well as label-free, sensitivity better than 1 ng/ml for Immunoglobulin G, and real-time analysis for protein interaction process, etc. provide a potential for applications in biomedicine field. The recent biosensing development with total internal reflection imaging ellipsometry is presented also. [GRAPHICS] An example of 48 protein arrays in matrix. (C) 2008 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Two Nuclear Localization Signals in USP1 Mediate Nuclear Import of the USP1/UAF1 Complex

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An automatic imaging spectroscopic ellipsometer for characterization of nano-film pattern on solid substrate

In order to characterize the physical and spatial properties of nano-film pattern on solid substrates, an automatic imaging spectroscopic ellipsometer (ISE) based on a polarizer - compensator - specimen - analyzer configuration in the visible region is presented. It can provide the spectroscopic ellipsometric parameters psi (x, y, lambda) and Delta (x, y, lambda) of a large area specimen with a lateral resolution in the order of some microns. A SiO2 stepped layers pattern is used to demonstrate the function of the ISE which shows potential application in thin film devices' such as high-throughput bio-chips.

Wide Screening of Phage-Displayed Libraries Identifies Immune Targets in Planta

Microbe-Associated Molecular Patterns and virulence effectors are recognized by plants as a first step to mount a defence response against potential pathogens. This recognition involves a large family of extracellular membrane receptors and other immune proteins located in different sub-cellular compartments. We have used phage-display technology to express and select for Arabidopsis proteins able to bind bacterial pathogens. To rapidly identify microbe-bound phage, we developed a monitoring method based on microarrays. This combined strategy allowed for a genome-wide screening of plant proteins involved in pathogen perception. Two phage libraries for high-throughput selection were constructed from cDNA of plants infected with Pseudomonas aeruginosa PA14, or from combined samples of the virulent isolate DC3000 of Pseudomonas syringae pv. tomato and its avirulent variant avrRpt2. These three pathosystems represent different degrees in the specificity of plant-microbe interactions. Libraries cover up to 26107 different plant transcripts that can be displayed as functional proteins on the surface of T7 bacteriophage. A number of these were selected in a bio-panning assay for binding to Pseudomonas cells. Among the selected clones we isolated the ethylene response factor ATERF-1, which was able to bind the three bacterial strains in competition assays. ATERF-1 was rapidly exported from the nucleus upon infiltration of either alive or heat-killed Pseudomonas. Moreover, aterf-1 mutants exhibited enhanced susceptibility to infection. These findings suggest that ATERF-1 contains a microbe-recognition domain with a role in plant defence. To identify other putative pathogen-binding proteins on a genome-wide scale, the copy number of selected-vs.-total clones was compared by hybridizing phage cDNAs with Arabidopsis microarrays. Microarray analysis revealed a set of 472 candidates with significant fold change. Within this set defence-related genes, including well-known targets of bacterial effectors, are over-represented. Other genes non-previously related to defence can be associated through this study with general or strain-specific recognition of Pseudomonas.

Detection of hepatitis B virus markers using a biosensor based on imaging ellipsometry

A biosensor based on imaging ellipsometry (BIE) has been developed and validated in 169 patients for detecting five markers of hepatitis B virus (HBV) infection. The methodology has been established to pave the way for clinical diagnosis, including ligand screening, determination of the sensitivity, set-up of cut-off values (CoVs) and comparison with other clinical methods. A matrix assay method was established for ligand screening. The CoVs of HBV markers were derived with the help of receiver operating characteristic curves. Enzyme-linked immunosorbent assay (ELISA) was the reference method. Ligands with high bioactivity were selected and sensitivities of 1 ng/mL and 1 IU/mL for hepatitis B surface antigen (HBsAg) and surface antibody (anti-HBs) were obtained respectively. The CoVs of HBsAg, anti-HBs, hepatitis B e antigen, hepatitis B e antibody and core antibody were as follows: 15%, 18%, 15%, 20% and 15%, respectively, which were the percentages over the values of corresponding ligand controls. BIE can simultaneously detect up to five markers within 1 h with results in acceptable agreement with ELISA, and thus shows a potential for diagnosing hepatitis B with high throughput.