β-turn tendency in N-methylated peptides with dehydrophenylalanine residue: DFT study

The tendency to adopt β‐turn conformation by model dipeptides with α,β‐dehydrophenylalanine (ΔPhe) residue in the gas phase and in solution is investigated by theoretical methods. We pay special attention to a dependence of conformational properties on the side‐chain configuration of dehydro residue and the influence of N‐methylation on β‐turn stability. An extensive computational study of the conformational preferences of Z and E isomers of dipeptides Ac‐Gly‐(E/Z)‐ΔPhe‐NHMe ( 1a / 1b ) and Ac‐Gly‐(E/Z)‐ΔPhe‐NMe₂ ( 2a / 2b ) by B3LYP/6‐311++G(d,p) and MP2/6‐311++G(d,p) methods is reported. It is shown that, in agreement with experimental data, Ac‐Gly‐(Z)‐ΔPhe‐NHMe has a great tendency to adopt β‐turn conformation. In the gas phase the type II β‐turn is preferred, whereas in the polar environment, the type I. On the other hand, dehydro residue in Ac‐Gly‐(E)‐ΔPhe‐NHMe has a preference to adopt extended conformations in all environments. N‐methylation of C‐terminal amide group, which prevents the formation of 1←4 intramolecular hydrogen bond, change dramatically the conformational properties of studied dehydropeptides. Especially, the tendency to adopt β‐turn conformations is much weaker for the N‐methylated Z isomer (Ac‐Gly‐(Z)‐ΔPhe‐NMe₂), both in vacuo and in the polar environment. On the contrary, N‐methylated E isomer (Ac‐Gly‐(E)‐ΔPhe‐NMe₂) can easier adopt β‐turn conformation, but the backbone torsion angles (?₁, ψ₁, ?₂, ψ₂) are off the limits for common β‐turn types. © 2012 Wiley Periodicals, Inc. Biopolymers 97:518–528, 2012.     

Single-step methods for genomic evaluation in pigs

Genetic evaluation based on information from phenotypes, pedigree and markers can be implemented using a recently developed single-step method. In this paper we compare accuracies of predicted breeding values for daily gain and feed conversion ratio (FCR) in Danish Duroc pigs obtained from different versions of single-step methods, the traditional pedigree-based method and the genomic BLUP (GBLUP) method. In particular, we present a single-step method with an adjustment of the genomic relationship matrix so that it is compatible to the pedigree-based relationship matrix. Comparisons are made for both genotyped and non-genotyped animals and univariate and bivariate models. The results show that the three methods with marker information (two single-step methods and GBLUP) produce more accurate predictions of genotyped animals than the pedigree-based method. In addition, single-step methods provide more accurate predictions for non-genotyped animals. The results also show that the single-step method with adjusted genomic relationship matrix produce more accurate predictions than the original single-step method. Finally, the results for the bivariate analyses show a somewhat improved accuracy and reduced inflation of predictions for FCR for the two single-step methods compared with the univariate analyses. The conclusions are: first, the methods with marker information improve prediction compared with the pedigree-based method; second, a single-step method, contrary to GBLUP, provides improved predictions for all animals compared to the pedigree-based method; and third, a single-step method should be used with an adjustment of the genomic relationship matrix.     

Strategies for membrane interaction proteomics: no mass spectrometry required

Membrane-bound proteins are one of the most important protein types in the cell, and are involved in many major cell processes and signaling pathways. Most proteins, including those at membranes, must interact with other proteins to form complexes, which are essential for their function(s). In this review, we describe some of the major non-mass spectrometry-based methods and technologies used for the investigation of intracellular membrane protein complexes including Tango, fluorescence/bioluminescence resonance energy transfer (F/BRET), luminescence-based mammalian interactome mapping (LUMIER), protein-fragment complementation assay (PCA), and membrane yeast two-hybrid assay (MYTH). We highlight the advantages and drawbacks of these methods, describe recent studies utilizing these methods, and discuss some of the major findings in the study of membrane protein-based cell pathways.     

Chaotic dynamics of a three species prey-predator competition model with bionomic harvesting due to delayed environmental noise as external driving force

We consider a biological economic model based on prey-predator interactions to study the dynamical behaviour of a fishery resource system consisting of one prey and two predators surviving on the same prey. The mathematical model is a set of first order non-linear differential equations in three variables with the population densities of one prey and the two predators. All the possible equilibrium points of the model are identified, where the local and global stabilities are investigated. Biological and bionomical equilibriums of the system are also derived. We have analysed the population intensities of fluctuations i.e., variances around the positive equilibrium due to noise with incorporation of a constant delay leading to chaos, and lastly have investigated the stability and chaotic phenomena with a computer simulation.     

Developing bioimaging and quantitative methods to study 3D genome

The recent advances in chromosome configuration capture (3C)-based series molecular methods and optical super-resolution (SR) techniques offer powerful tools to investigate three dimensional (3D) genomic structure in prokaryotic and eukaryotic cell nucleus. In this review, we focus on the progress during the last decade in this exciting field. Here we at first introduce briefly genome organization at chromosome, domain and sub-domain level, respectively; then we provide a short introduction to various super-resolution microscopy techniques which can be employed to detect genome 3D structure. We also reviewed the progress of quantitative and visualization tools to evaluate and visualize chromatin interactions in 3D genome derived from Hi-C data. We end up with the discussion that imaging methods and 3C-based molecular methods are not mutually exclusive - - - - actually they are complemental to each other and can be combined together to study 3D genome organization.     

Microbial Source Tracking for Identification of Fecal Pollution

Fecal pollution is a serious environmental problem that affects many coastal and inland waters worldwide. Both human and animal fecal pollution impose risks to human health from exposure to pathogenic bacteria, viruses, and protozoa. To assist authorities with the implementation of the changes suggested by more restricted legislation concering water quality in Europe, methods are needed which can identify the sources of fecal pollution. Management of fecal contamination of water would be improved if the origin of the fecal pollution could be correctly identified since remediation efforts could then be allocated in a more effective manner. The concept that the origin of fecal pollution can be traced has been termed microbial source tracking. In microbial source tracking (MST) endogenous markers of fecal sources are used for identification of the fecal pollution in aquatic environments. Chemical MST-methods can be used to trace mainly sewage pollution, but the used chemical targets have no direct relationship with pathogenic bacteria. This is not the case in microbial MST-methods where source-specific bacteria or viruses are cultured to identify fecal pollution sources. However, sometimes these microbial targets can be present in too low numbers to be detected. This is circumvented by using molecular assays for host-specific marker detection. Phenotypic and genotypic library-based methods can be used to discriminate among different fecal sources. However, the isolation step makes this procedure very labour-intensive, and issues as temporal and geographical variability remain unresolved. The underlying assumptions will be discussed and the methods mostly used in microbial source tracking will be described in more detail.     

CORRELATED EVOLUTION OF GENOME SIZE AND CELL VOLUME IN DIATOMS (BACILLARIOPHYCEAE)1

A correlation between genome size and cell volume has been observed across diverse assemblages of eukaryotes. We examined this relationship in diatoms (Bacillariophyceae), a phylum in which cell volume is of critical ecological and biogeochemical importance. In addition to testing whether there is a predictive relationship across extant species, we tested whether evolutionary divergences in genome size were correlated with evolutionary divergences in cell size (using independent contrasts). We estimated total DNA content for 16 diatom species using a flow cytometer and estimated cell volumes using critical dimensions with scaling equations. Our independent contrast analyses indicated a significant correlated evolution between genome size and cell volume. We then explored the evolutionary and ecological implications of this evolutionary relationship. Diatom cell volume is an important component of the global carbon cycle; therefore, understanding the mechanisms that drive diatom genome evolution has both evolutionary and ecological importance.     

Bayesian hierarchical spatially correlated functional data analysis with application to colon carcinogenesis

Summary .   In this article, we present new methods to analyze data from an experiment using rodent models to investigate the role of p27, an important cell-cycle mediator, in early colon carcinogenesis. The responses modeled here are essentially functions nested within a two-stage hierarchy. Standard functional data analysis literature focuses on a single stage of hierarchy and conditionally independent functions with near white noise. However, in our experiment, there is substantial biological motivation for the existence of spatial correlation among the functions, which arise from the locations of biological structures called colonic crypts: this possible functional correlation is a phenomenon we term crypt signaling . Thus, as a point of general methodology, we require an analysis that allows for functions to be correlated at the deepest level of the hierarchy. Our approach is fully Bayesian and uses Markov chain Monte Carlo methods for inference and estimation. Analysis of this data set gives new insights into the structure of p27 expression in early colon carcinogenesis and suggests the existence of significant crypt signaling. Our methodology uses regression splines, and because of the hierarchical nature of the data, dimension reduction of the covariance matrix of the spline coefficients is important: we suggest simple methods for overcoming this problem.     

Determining the effective sample size of a parametric prior

Summary .   We present a definition for the effective sample size of a parametric prior distribution in a Bayesian model, and propose methods for computing the effective sample size in a variety of settings. Our approach first constructs a prior chosen to be vague in a suitable sense, and updates this prior to obtain a sequence of posteriors corresponding to each of a range of sample sizes. We then compute a distance between each posterior and the parametric prior, defined in terms of the curvature of the logarithm of each distribution, and the posterior minimizing the distance defines the effective sample size of the prior. For cases where the distance cannot be computed analytically, we provide a numerical approximation based on Monte Carlo simulation. We provide general guidelines for application, illustrate the method in several standard cases where the answer seems obvious, and then apply it to some nonstandard settings.     

Orientation of collagen at the osteocyte lacunae in human secondary osteons

This work characterizes an aspect of human bone micro-structure, pertinent to fracture initiation and arrest. It addresses how the orientation of elementary components proximate to osteocyte lacunae influences secondary osteon micro-biomechanics. New data at the perilacunar region concerning orientation of collagen-apatite, and prior data on collagen orientation outside the perilacunar region, are incorporated in a novel simulation of osteons to investigate how orientation relates to strains and stresses during mechanical testing. The perilacunar region was observed by confocal microscopy within single lamellar specimens, isolated from osteons. The specimens were separated by extinct or bright appearance in transverse section under circularly polarizing light. This is because synchrotron diffraction and confocal microscopy had established that each type, away from the perilacunar region, corresponds to specific dominant collagen orientation (extinct lamellae's dominant collagen forming small angles with the original osteon axis, while the bright lamellae's forms larger angles). Morphometry of serial confocal images of each perilacunar region showed collagen orientation generally following the orientation of canaliculi, circumambiently-perpendicular to the lacuna. The lacunae tilted relative to the lamellar walls were more numerous in extinct than in bright lamella. Their apices were less likely in extinct than bright lamella to show collagen following the canalicular orientation. The simulation of osteocyte lacunae in osteons, under tension or compression loading, supports the hypothesis that collagen orientation affects strains and stresses at the equatorial perilacunar region in conjunction with the presence of the lacuna. We further conjecture that collagen orientation diverts propagation of micro-cracks initiating from apices.