A PCR-directed cell-free approach to optimize protein expression using diverse fusion tags

N-terminal fusion tags that enhance translation initiation or protein solubility are often used to facilitate protein overexpression. As the optimal tag for a given target protein cannot be predicted a priori, valuable time can be lost in cloning and manipulating the corresponding gene to generate different fusion constructs for expression analysis. We have developed a cell-free strategy that consolidates these steps, enabling the utility of a panel of nine fusion-tags to be determined within one to two days. This approach exploits the fact that PCR-amplified DNA can be used as a template for cell-free protein synthesis. Overlap/extension PCR using the TEV protease site as the overlap region allows the fusion of different T7 promoter (T7p)-tag-TEV DNA fragments with a TEV-gene-T7 terminator (T7ter) fragment. For tag sequences where the TEV site is not compatible, a short C?G? repeat (CGr) sequence can be used as the overlap region. The resulting T7p-tag-TEV-gene-T7ter constructs are then used as templates for PCR-directed cell-free protein synthesis to identify which tag-TEV-gene fusion protein produces the highest amount of soluble protein. We have successfully applied this approach to the overexpression of the Adiponectin hypervariable domain (AHD). Five of the nine N-terminal fusion tags tested enabled the synthesis of soluble recombinant protein. The best of these was the Peptidyl-prolylcis-trans isomerise B (PpiB) fusion tag which produces 1mg/ml amounts of soluble fusion protein. PpiB is an example of a new class of fusion tag known as the "stress-responsive proteins". Our results suggest that this cell-free fusion-tag expression screen facilitates the rapid identification of suitable fusion-tags that overcome issues such as poor expression and insolubility, often encountered using conventional approaches.     

A top-down approach to classify enzyme functional classes and sub-classes using random forest

Advancements in sequencing technologies have witnessed an exponential rise in the number of newly found enzymes. Enzymes are proteins that catalyze bio-chemical reactions and play an important role in metabolic pathways. Commonly, function of such enzymes is determined by experiments that can be time consuming and costly. Hence, a need for a computing method is felt that can distinguish protein enzyme sequences from those of non-enzymes and reliably predict the function of the former. To address this problem, approaches that cluster enzymes based on their sequence and structural similarity have been presented. But, these approaches are known to fail for proteins that perform the same function and are dissimilar in their sequence and structure. In this article, we present a supervised machine learning model to predict the function class and sub-class of enzymes based on a set of 73 sequence-derived features. The functional classes are as defined by International Union of Biochemistry and Molecular Biology. Using an efficient data mining algorithm called random forest, we construct a top-down three layer model where the top layer classifies a query protein sequence as an enzyme or non-enzyme, the second layer predicts the main function class and bottom layer further predicts the sub-function class. The model reported overall classification accuracy of 94.87% for the first level, 87.7% for the second, and 84.25% for the bottom level. Our results compare very well with existing methods, and in many cases report better performance. Using feature selection methods, we have shown the biological relevance of a few of the top rank attributes.     

Defective guanine uptake in an 8-azaguanine-resistant mutant of Salmonella typhimurium

An 8-azaguanine-resistant mutant, azg-11, derived from a guanine auxotroph, gua-1, of Salmonella typhimurium was isolated. This mutant was resistant to the analogue when grown on 2,6-diaminopurine, but showed greater susceptibility than the parent on guanine. Studies with the uptake of radioactive purines revealed that the mutant was defective in a mechanism for incorporation of guanine as well as of xanthine. Initial rates of uptake were determined for guanine at concentrations which were sufficiently low to make permeases limiting. The affinity constant K(m) for the mutant was found to be 2.5 x 10(-4)m; that of the parent was 2.3 x 10(-5)m. Examination of cell-free extracts suggested that the purine nucleotide pyrophosphorylases, responsible for the conversion of free intracellular purines to the corresponding nucleotides, were present and unaltered. The results indicate that the mutant is defective in a mechanism for the active transport for guanine and possibly xanthine.     

Computational Analysis of C-Reactive Protein for Assessment of Molecular Dynamics and Interaction Properties

Serum C-reactive protein (CRP) is used as a marker of inflammation in several diseases including autoimmune disease and cardiovascular disease. CRP, a member of the pentraxin family, is comprised of five identical subunits. CRP has diverse ligand-binding properties which depend upon different structural states of CRP. However, little is known about the molecular dynamics and interaction properties of CRP. In this study, we used SAPS, SCRATCH protein predictor, PDBsum, ConSurf, ProtScale, Drawhca, ASAView, SCide and SRide server and performed comprehensive analyses of molecular dynamics, protein–protein and residue–residue interactions of CRP. We used 1GNH.pdb file for the crystal structure of human CRP which generated two pentamers (ABCDE and FGHIJ). The number of residues involved in residue–residue interactions between A–B, B–C, C–D, D–E, F–G, G–H, H–I, I–J, A–E and F–J subunits were 12, 11, 10, 11, 12, 11, 10, 11, 10 and 10, respectively. Fifteen antiparallel β sheets were involved in β-sheet topology, and five β hairpins were involved in forming the secondary structure. Analysis of hydrophobic segment distribution revealed deviations in surface hydrophobicity at different cavities present in CRP. Approximately 33 % of all residues were involved in the stabilization centers. We show that the bioinformatics tools can provide a rapid method to predict molecular dynamics and interaction properties of CRP. Our prediction of molecular dynamics and interaction properties of CRP combined with the modeling data based on the known 3D structure of CRP is helpful in designing stable forms of CRP mutants for structure–function studies of CRP and may facilitate in silico drug design for therapeutic targeting of CRP.     

IGFBP3 gene promoter methylation analysis and its association with clinicopathological characteristics of colorectal carcinoma

Molecular Biology Reports - Promoter methylation mediated silencing of tumor suppressor genes plays an important role in the tumorigenesis of colorectal carcinoma (CRC). Tumor suppressor gene,...     

Modeling in vitro cholesterol reduction in relation to growth of probiotic Lactobacillus casei

Lactobacillus casei LA‐1 isolated from a nondairy fermented source was evaluated for its in vitro ability to reduce cholesterol. The bacterium tested positive for bile salt deconjugation in relation to cholesterol removal. Tested growth‐associated physiological variables such as pH, temperature and inoculum size were all found to have significant effects on in vitro cholesterol reduction and biomass production (both P < 0.005). Furthermore, a central composite design was used to evaluate the effects of significant variables and their interactions. A linear regression model was developed for in vitro cholesterol reduction as a function of growth‐associated variables. Maximum cholesterol reduction achieved was 45% whereas maximum biomass yield of 2.34 optical density was observed at the central point. Our study possibly indicates that the growth of L. casei LA‐1 depends on its cholesterol removing ability.     

Study of Surface Enhanced Raman Scattering of Single Molecule Adsorbed on the Surface of Metal Nanogeometries: Electrostatic Approach

Plasmonics - In this paper, we have studied the surface enhanced raman scattering (SERS) from a molecule adsorbed on coated and non-coated spherical shape metallic nanoparticles. We have accounted...     

Numerical Simulation of Broadband Scattering by Coated and Noncoated Metal Nanostructures Using Discrete Dipole Approximation Method

We suggest numerical method to study the optical response of metal nanostructures. The analysis of optical properties such as scattering and absorption by coated and noncoated nanogeometry has been done using discrete dipole approximation (DDA) method. The core-shell nanogeometry supports surface plasmon resonances, which are highly tunable from 400 to 1100 nm. The tunability of surface plasmon resonance (SPR) highly depends on the structural anisotropy and chosen core-shell material. Further, we have observed that aspect ratio is one of the key parameter to decide the nature and position of the plasmonic peaks and magnitude of optical cross section. We have also shown that coated nanospheroid is a more appropriate geometry as compared to coated nanosphere and noncoated nanospheroid in terms of wide tunability of surface plasmon resonance. The wide tunability in SPR is observed for the effective radii 90 nm core-shell (Au@SiO₂) nanospheroid with aspect ratio 0.1.     

Endophytes of opium poppy differentially modulate host plant productivity and genes for the biosynthetic pathway of benzylisoquinoline alkaloids

Planta - Endophytes reside in different parts of the poppy plant and perform the tissue-specific functions. Most leaf endophytes modulate photosynthetic efficiency, plant growth, and productivity...     

Structural characterization and oligomerization of PB1-F2, a proapoptotic influenza A virus protein

Recently, a novel 87-amino acid influenza A virus protein with proapoptotic properties, PB1-F2, has been reported that originates from an alternative reading frame in the PB1 polymerase gene and is encoded in most known human influenza A virus isolates. Here we characterize the molecular structure of a biologically active synthetic version of the protein (sPB1-F2). Western blot analysis, chemical cross-linking, and NMR spectroscopy afforded direct evidence of the inherent tendency of sPB1-F2 to undergo oligomerization mediated by two distinct domains located in the N and C termini, respectively. CD and (1)H NMR spectroscopic analyses indicate that the stability of structured regions in the molecule clearly depends upon the hydrophobicity of the solvent. In aqueous solutions, the behavior of sPB1-F2 is typical of a largely random coil peptide that, however, adopts alpha-helical structure upon the addition of membrane mimetics. (1)H NMR analysis of three overlapping peptides afforded, for the first time, direct experimental evidence of the presence of a C-terminal region with strong alpha-helical propensity comprising amino acid residues Ile(55)-Lys(85) connected via an essentially random coil structure to a much weaker helix-like region, located in the N terminus between residues Trp(9) and Lys(20). The C-terminal helix is not a true amphipathic helix and is more compact than previously predicted. It corresponds to a positively charged region previously shown to include the mitochondrial targeting sequence of PB1-F2. The consequences of the strong oligomerization and helical propensities of the molecule are discussed and used to formulate a hypothetical model of its interaction with the mitochondrial membrane.