Next-generation optical microscopy

A new breed of microscopy techniques is coming to the forefront of optical imaging. They enhance the attainable 3D resolution of imaging in live and ``fixed'' cells' (with minimal structural perturbation) by greater than tenfold, bringing subcellular structures in sharp focus Along with long-term imaging, deep tissue and high throughput capablities, new insights in various fields of biology are being generated. The main set of these next-generation optical microscopy techniques along with select applications is described in this article.

A fast NMR method for resonance assignments: application to metabolomics

We present a new method for rapid NMR data acquisition and assignments applicable to unlabeled (C-12) or C-13-labeled biomolecules/organic molecules in general and metabolomics in particular. The method involves the acquisition of three two dimensional (2D) NMR spectra simultaneously using a dual receiver system. The three spectra, namely: (1) G-matrix Fourier transform (GFT) (3,2)D C-13, H-1] HSQC-TOCSY, (2) 2D H-1-H-1 TOCSY and (3) 2D C-13-H-1 HETCOR are acquired in a single experiment and provide mutually complementary information to completely assign individual metabolites in a mixture. The GFT (3,2)D C-13, H-1] HSQC-TOCSY provides 3D correlations in a reduced dimensionality manner facilitating high resolution and unambiguous assignments. The experiments were applied for complete H-1 and C-13 assignments of a mixture of 21 unlabeled metabolites corresponding to a medium used in assisted reproductive technology. Taken together, the experiments provide time gain of order of magnitudes compared to the conventional data acquisition methods and can be combined with other fast NMR techniques such as non-uniform sampling and covariance spectroscopy. This provides new avenues for using multiple receivers and projection NMR techniques for high-throughput approaches in metabolomics.

Combinatorial Exploration of the Structural Landscape of Acid-Pyridine Cocrystals

The structural landscape of acid-pyridine cocrystals is explored by adopting a combinatorial matrix method with 4-substituted benzoic acids and 4-substituted pyridines. The choice of the system restricts the primary synthon to the robust acid-pyridine entity. This methodology accordingly provides hints toward the formation of secondary synthons. The pK(a) rule is validated in the landscape by taking all components of the matrix together and exploring it as a whole. Along with the global features, the exploration of landscapes reveals some local features. Apart from the identification of secondary synthons, it also sheds light on the propensity of hydration in cocrystals, synthon competition, and certain topological similarities. The method described here combines two approaches, namely, database analysis and high throughput crystallography, to extract more information with minimal extra experimental effort.

A framework for post-silicon realization of arbitrary instruction extensions on reconfigurable data-paths

In this paper we present a framework for realizing arbitrary instruction set extensions (IE) that are identified post-silicon. The proposed framework has two components viz., an IE synthesis methodology and the architecture of a reconfigurable data-path for realization of the such IEs. The IE synthesis methodology ensures maximal utilization of resources on the reconfigurable data-path. In this context we present the techniques used to realize IEs for applications that demand high throughput or those that must process data streams. The reconfigurable hardware called HyperCell comprises a reconfigurable execution fabric. The fabric is a collection of interconnected compute units. A typical use case of HyperCell is where it acts as a co-processor with a host and accelerates execution of IEs that are defined post-silicon. We demonstrate the effectiveness of our approach by evaluating the performance of some well-known integer kernels that are realized as IEs on HyperCell. Our methodology for realizing IEs through HyperCells permits overlapping of potentially all memory transactions with computations. We show significant improvement in performance for streaming applications over general purpose processor based solutions, by fully pipelining the data-path. (C) 2014 Elsevier B.V. All rights reserved.

Cancer gene signatures in risk stratification: use in personalized medicine

Cancer is a complex disease which arises due to a series of genetic changes related to cell division and growth control. Cancer remains the second leading cause of death in humans next to heart diseases. As a testimony to our progress in understanding the biology of cancer and developments in cancer diagnosis and treatment methods, the overall median survival time of all cancers has increased six fold one year to six years during the last four decades. However, while the median survival time has increased dramatically for some cancers like breast and colon, there has been only little change for other cancers like pancreas and brain. Further, not all patients having a single type of tumour respond to the standard treatment. The differential response is due to genetic heterogeneity which exists not only between tumours, which is called intertumour heterogeneity, but also within individual tumours, which is called intratumoural heterogeneity. Thus it becomes essential to personalize the cancer treatment based on a specific genetic change in a given tumour. It is also possible to stratify cancer patients into low- and high-risk groups based on expression changes or alterations in a group of genes gene signatures and choose a more suitable mode of therapy. It is now possible that each tumour can be analysed using various high-throughput methods like gene expression profiling and next-generation sequencing to identify its unique fingerprint based on which a personalized or tailor-made therapy can be developed. Here, we review the important progress made in the recent years towards personalizing cancer treatment with the use of gene signatures.

Stable Crystalline Salts of Haloperidol: A Highly Water-Soluble Mesylate Salt

Haloperidol, an antipsychotic drug, was screened for new solid crystalline phases using high throughput crystallization in pursuit of solubility improvement. Due to the highly basic nature of the API, all the solid forms with acids were obtained in the form of salts. Eleven crystalline salts in the form of oxalate (1:1), benzoate (1:1), salicylate (1:1 and 1:2), 4-hydroxybenzoate (1:1), 4-hydroxybenzoate ethyl acetate solvate (1:1:1), 3,4-dihydroxybenzoate (1:1), 3,5-dihydroxybenzoate (1:1), mesylate (1:1), besylate (1:1), and tosylate (1:1) salt were achieved. There is an insertion of carboxylate or sulfonate anion into the hydrogen bonding pattern of haloperidol. The salts with the aliphatic carboxylic acids were found to be more prone to form salt hydrates compared with aromatic carboxylate salts. All the salts were subjected to solubility measurement in water at neutral pH. There was no direct correlation observed between the solubility of the salt and its coformer. All the salts are stable at room temperature as well as after 24 h slurry experiment except the oxalate salt, which showed an unusual phase transformation from its hydrated form to the anhydrous form. A structureproperty relationship was examined to analyze the solubility behavior of the solid forms.

De novo inference of protein function from coarse-grained dynamics

Inference of molecular function of proteins is the fundamental task in the quest for understanding cellular processes. The task is getting increasingly difficult with thousands of new proteins discovered each day. The difficulty arises primarily due to lack of high-throughput experimental technique for assessing protein molecular function, a lacunae that computational approaches are trying hard to fill. The latter too faces a major bottleneck in absence of clear evidence based on evolutionary information. Here we propose a de novo approach to annotate protein molecular function through structural dynamics match for a pair of segments from two dissimilar proteins, which may share even <10% sequence identity. To screen these matches, corresponding 1 mu s coarse-grained (CG) molecular dynamics trajectories were used to compute normalized root-mean-square-fluctuation graphs and select mobile segments, which were, thereafter, matched for all pairs using unweighted three-dimensional autocorrelation vectors. Our in-house custom-built forcefield (FF), extensively validated against dynamics information obtained from experimental nuclear magnetic resonance data, was specifically used to generate the CG dynamics trajectories. The test for correspondence of dynamics-signature of protein segments and function revealed 87% true positive rate and 93.5% true negative rate, on a dataset of 60 experimentally validated proteins, including moonlighting proteins and those with novel functional motifs. A random test against 315 unique fold/function proteins for a negative test gave >99% true recall. A blind prediction on a novel protein appears consistent with additional evidences retrieved therein. This is the first proof-of-principle of generalized use of structural dynamics for inferring protein molecular function leveraging our custom-made CG FF, useful to all. (C) 2014 Wiley Periodicals, Inc.

Organic photovoltaics: key photophysical, device and design aspects

Key aspects of Organic Photovoltaics (OPVs) have been reviewed in this tutorial. Issues pertaining to the choice of materials, fabrication processes, photophysical mechanisms, device characterization, morphology of active layers and manufacturing are discussed. Special emphasis has been given to recent developments in large-area modules. Current strategies in enhancing the performance using external optical engineering approaches have also been highlighted. OPVs as a technology combine low weight, flexibility, low cost, good form factor and high-throughput processing; making them a promising PV technology for the future.

Indigenous Development of an Imaging Flow Cytometer for Clinical and Biological Applications

Flow cytometry is a benchmark technique used for basic research and clinical diagnosis of various diseases. Despite being a high-throughput technique, it fails in capturing the morphology of cells being analyzed. Imaging flow cytometry is a combination of flow-cytometry and digital microscopy, which offers advantages of both the techniques. In this paper, we report on the development of an indigenous Imaging Flow Cytometer, realized with the combination of Optics, Microfluidics, and High-speed imaging. A custom-made bright-field transmission microscope is used to capture images of cells flowing across the microfluidic device. High-throughput morphological analysis on suspension of yeast cells is presented.

Graded IR Filters: Distinguishing Between Single and Multipoint NO2 center dot center dot center dot I Halogen Bonded Supramolecular Synthons (P, Q, and R Synthons)

The NO2 center dot center dot center dot I supramolecular synthon is a halogen bonded recognition pattern that is present in the crystal structures of many compounds that contain these functional groups. These synthons have been previously distinguished as P, Q, and R types using topological and geometrical criteria. A five step IR spectroscopic sequence is proposed here to distinguish between these synthon types in solid samples. Sets of known compounds that contain the P, Q, and R synthons are first taken to develop IR spectroscopic identifiers for them. The identifiers are then used to create graded IR filters that sieve the synthons. These filters contain signatures of the individual NO2 center dot center dot center dot I synthons and may be applied to distinguish between P, Q, and R synthon varieties. They are also useful to identify synthons that are of a borderline character, synthons in disordered structures wherein the crystal structure in itself is not sufficient to distinguish synthon types, and in the identification of the NO2 center dot center dot center dot I synthons in compounds with unknown crystal structures. This study establishes clear differences for the three different geometries P, Q, and Rand in the chemical differences in the intermolecular interactions contained in the synthons. Our IR method can be conveniently employed when single crystals are not readily available also in high throughput analysis. It is possible that such identification may also be adopted as an input for crystal structure prediction analysis of compounds with unknown crystal structures.

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.