Evolutionary and biochemical differences between human and monkey acidic mammalian chitinases

Acidic mammalian chitinase (AMCase), an enzyme implicated in the pathology of asthma, is capable of chitin cleavage at a low pH optimum. The corresponding gene (CHIA) can be found in genome databases of a variety of mammals, but the enzyme properties of only the human and mouse proteins were extensively studied. We wanted to compare enzymes of closely related species, such as humans and macaques. In our attempt to study macaque AMCase, we searched for CHIA-like genes in human and macaque genomes. We found that both genomes contain several additional CHIA-like sequences. In humans, CHIA-L1 (hCHIA-L1) is an apparent pseudogene and has the highest homology to CHIA. To determine which of the two genes is functional in monkeys, we assessed their tissue expression levels. In our experiments, CHIA-L1 expression was not detected in human stomach tissue, while CHIA was expressed at high levels. However, in the cynomolgus macaque stomach tissue, the expression pattern of these two genes was reversed: CHIA-L1 was expressed at high levels and CHIA was undetectable. We hypothesized that in macaques CHIA-L1 (mCHIA-L1), and not CHIA, is a gene encoding an acidic chitinase, and cloned it, using the sequence of human CHIA-L1 as a guide for the primer design. We named the new enzyme MACase (Macaca Acidic Chitinase) to emphasize its differences from AMCase. MACase shares a similar tissue expression pattern and pH optimum with human AMCase, but is 50 times more active in our enzymatic activity assay. DNA sequence of the mCHIA-L1 has higher percentage identity to the human pseudogene hCHIA-L1 (91.7%) than to hCHIA (84%). Our results suggest alternate evolutionary paths for human and monkey acidic chitinases.     

Recent models for adaptive personality differences: a review

In this paper we review recent models that provide adaptive explanations for animal personalities: individual differences in behaviour (or suites of correlated behaviours) that are consistent over time or contexts. We start by briefly discussing patterns of variation in behaviour that have been documented in natural populations. In the main part of the paper we discuss models for personality differences that (i) explain animal personalities as adaptive behavioural responses to differences in state, (ii) investigate how feedbacks between state and behaviour can stabilize initial differences among individuals and (iii) provide adaptive explanations for animal personalities that are not based on state differences. Throughout, we focus on two basic questions. First, what is the basic conceptual idea underlying the model? Second, what are the key assumptions and predictions of the model? We conclude by discussing empirical features of personalities that have not yet been addressed by formal modelling. While this paper is primarily intended to guide empiricists through current adaptive theory, thereby stimulating empirical tests of these models, we hope it also inspires theoreticians to address aspects of personalities that have received little attention up to now.     

A Single Asparagine-Linked Glycosylation Site of the Severe Acute Respiratory Syndrome Coronavirus Spike Glycoprotein Facilitates Inhibition by Mannose-Binding Lectin through Multiple Mechanisms

Mannose-binding lectin (MBL) is a serum protein that plays an important role in host defenses as an opsonin and through activation of the complement system. The objective of this study was to assess the interactions between MBL and severe acute respiratory syndrome-coronavirus (SARS-CoV) spike (S) glycoprotein (SARS-S). MBL was found to selectively bind to retroviral particles pseudotyped with SARS-S. Unlike several other viral envelopes to which MBL can bind, both recombinant and plasma-derived human MBL directly inhibited SARS-S-mediated viral infection. Moreover, the interaction between MBL and SARS-S blocked viral binding to the C-type lectin, DC-SIGN. Mutagenesis indicated that a single N-linked glycosylation site, N330, was critical for the specific interactions between MBL and SARS-S. Despite the proximity of N330 to the receptor-binding motif of SARS-S, MBL did not affect interactions with the ACE2 receptor or cathepsin L-mediated activation of SARS-S-driven membrane fusion. Thus, binding of MBL to SARS-S may interfere with other early pre- or postreceptor-binding events necessary for efficient viral entry.A novel coronavirus (CoV), severe acute respiratory syndrome-CoV (SARS-CoV), is the causal agent of severe acute respiratory syndrome, which afflicted thousands of people worldwide in 2002 and 2003 (10, 39). SARS-CoV is an enveloped, single- and positive-strand RNA virus that encodes four major structural proteins: S, spike glycoprotein (GP); E, envelope protein; M, membrane glycoprotein; and N, nucleocapsid protein (46, 55). Similar to other coronaviruses, the S glycoprotein of the virus mediates the initial attachment of the virus to host cell receptors, angiotensin-converting enzyme 2 (ACE2) (44) and/or DC-SIGNR (dendritic cell-specific intercellular adhesion molecule 3-grabbing nonintegrin-related molecule; also CD209L or L-SIGN[liver/lymph node-SIGN]) (32) and subsequent fusion of the viral and cellular membranes to allow viral entry into susceptible target cells. The S glycoprotein of SARS-CoV (SARS-S) is a 1,255-amino-acid (aa) type I membrane glycoprotein (46) with 23 potential N-linked glycosylation sites (55). The S glycoproteins of some coronaviruses are translated as a large polypeptide that is subsequently proteolytically cleaved into two functional subunits, S1 (harboring the receptor-binding domain [RBD]) and S2 (containing the membrane fusion domains) (1, 31, 51), during biogenesis, but others are not. The S glycoprotein on mature SARS-CoV virions does not appear to be cleaved (50, 61), but sequence alignments with other coronavirus S glycoproteins allow definition of S1 and S2 regions (46, 55). More recently, studies showed the proteolysis of the S glycoprotein of SARS-CoV on mature virions by cathepsin L (CTSL) (28, 59), as well as trypsin (43, 61) and factor Xa (11), suggesting that a critical cleavage event may occur during cell entry rather than during virion biogenesis.Mannose-binding lectin (MBL; also known as mannose-binding or mannan-binding protein [MBP]) is a Ca²⁺-dependent (C-type) serum lectin that plays an important role in innate immunity by binding to carbohydrates on the surface of a wide range of pathogens (including bacteria, viruses, fungi, and protozoa) (8, 14, 18), where it activates the complement system or acts directly as an opsonin (30, 40, 52). In order to activate the complement system, MBL must be in complex with a group of MBL-associated serine proteases (MASPs), MASP-1, -2, and -3. Currently, only the role of MASP-2 in complement activation has been clearly defined (65). The MBL-MASP-2 complex cleaves C4 and C2 to form C3 convertase (C4bC2a), which, in turn, activates the downstream complement cascade. MBL is a pattern recognition molecule (9), and surface recognition is mediated through its C-terminal carbohydrate recognition domains (CRDs), which are linked to collagenous stems by a short coiled-coil of alpha-helices. MBL is a mixture of oligomers assembled from subunits that are formed from three identical polypeptide chains (9) and usually has two to six clusters of CRDs. Within each of the clusters, the carbohydrate-binding sites have a fixed orientation, which allows selective recognition of patterns of carbohydrate residues on the surfaces of a wide range of microorganisms (8, 14, 18). The concentration of MBL in the serum varies greatly and is affected by mutations of the promoter and coding regions of the human MBL gene (45). MBL deficiency is associated with susceptibility to various infections, as well as autoimmune, metabolic, and cardiovascular diseases, although MBL-deficient individuals are generally healthy (13, 37, 67).There are conflicting results with regard to the role of MBL in SARS-CoV infection (29, 42, 72, 73). While the association of MBL gene polymorphisms with susceptibility to SARS-CoV infection was reported in some studies (29, 73), Yuan et al. demonstrated that there were no significant differences in MBL genotypes and allele frequencies among SARS patients and controls (72). Ip et al. observed binding to, and inhibition of, SARS-CoV by MBL (29). However, in other studies, no binding of MBL to purified SARS-CoV S glycoprotein was detected (42).In this study, retroviral particles pseudotyped with SARS-S and in vitro assays were used to characterize the role of MBL in SARS-CoV infection. The data indicated that MBL selectively bound to SARS-S and mediated inhibition of viral infection in susceptible cell lines. Moreover, we identified a single N-linked glycosylation site, N330, on SARS-S that is critical for the specific interactions with MBL.     

Human Tau Isoforms Assemble into Ribbon-like Fibrils That Display Polymorphic Structure and Stability

Fibrous aggregates of Tau protein are characteristic features of Alzheimer disease. We applied high resolution atomic force and EM microscopy to study fibrils assembled from different human Tau isoforms and domains. All fibrils reveal structural polymorphism; the “thin twisted” and “thin smooth” fibrils resemble flat ribbons (cross-section ∼10 × 15 nm) with diverse twist periodicities. “Thick fibrils” show periodicities of ∼65–70 nm and thicknesses of ∼9–18 nm such as routinely reported for “paired helical filaments” but structurally resemble heavily twisted ribbons. Therefore, thin and thick fibrils assembled from different human Tau isoforms challenge current structural models of paired helical filaments. Furthermore, all Tau fibrils reveal axial subperiodicities of ∼17–19 nm and, upon exposure to mechanical stress or hydrophobic surfaces, disassemble into uniform fragments that remain connected by thin thread-like structures (∼2 nm). This hydrophobically induced disassembly is inhibited at enhanced electrolyte concentrations, indicating that the fragments resemble structural building blocks and the fibril integrity depends largely on hydrophobic and electrostatic interactions. Because full-length Tau and repeat domain constructs assemble into fibrils of similar thickness, the “fuzzy coat” of Tau protein termini surrounding the fibril axis is nearly invisible for atomic force microscopy and EM, presumably because of its high flexibility.     

The influence of sagittal center of pressure offset on gait kinematics and kinetics

ObjectivesKinetic patterns of the lower extremity joints have been shown to be influenced by modification of the location of the center of pressure (CoP) of the foot. The accepted theory is that a shifted location of the CoP alters the distance between the ground reaction force and the center of the joint, thereby modifying torques during gait. Various footwear designs have been reported to significantly alter the magnitude of sagittal joint torques during gait. However, the relationship between the CoP and the kinetic patterns in the sagittal plane has not been examined. The aim of this study was to evaluate the association between the sagittal location of the CoP and gait patterns during gait in healthy men.MethodsA foot-worn biomechanical device which allows controlled manipulation of the CoP location was utilized. Fourteen healthy men underwent successive gait analysis with the device set to convey three different sagittal locations of the CoP: neutral, anterior offset and posterior offset.ResultsCoP translation in the sagittal plane (i.e., from posterior to anterior) significantly related with an ankle dorsiflexion torque and a knee extension torque shift throughout the stance phase. Likewise, an anterior translation of the CoP significantly reduced the extension torque at the hip during pre-swing.ConclusionsThe study results confirm a direct correlation between sagittal offset of the CoP and the magnitude of joint torques throughout the lower extremity.     

Airway Surface Liquid Volume Regulation Determines Different Airway Phenotypes in Liddle Compared with βENaC-overexpressing Mice

Studies in cystic fibrosis patients and mice overexpressing the epithelial Na⁺ channel β-subunit (βENaC-Tg) suggest that raised airway Na⁺ transport and airway surface liquid (ASL) depletion are central to the pathogenesis of cystic fibrosis lung disease. However, patients or mice with Liddle gain-of-function βENaC mutations exhibit hypertension but no lung disease. To investigate this apparent paradox, we compared the airway phenotype (nasal versus tracheal) of Liddle with CFTR-null, βENaC-Tg, and double mutant mice. In mouse nasal epithelium, the region that functionally mimics human airways, high levels of CFTR expression inhibited Liddle epithelial Nat channel (ENaC) hyperfunction. Conversely, in mouse trachea, low levels of CFTR failed to suppress Liddle ENaC hyperfunction. Indeed, Na⁺ transport measured in Ussing chambers (“flooded” conditions) was raised in both Liddle and βENaC-Tg mice. Because enhanced Na⁺ transport did not correlate with lung disease in these mutant mice, measurements in tracheal cultures under physiologic “thin film” conditions and in vivo were performed. Regulation of ASL volume and ENaC-mediated Na⁺ absorption were intact in Liddle but defective in βENaC-Tg mice. We conclude that the capacity to regulate Na⁺ transport and ASL volume, not absolute Na⁺ transport rates in Ussing chambers, is the key physiologic function protecting airways from dehydration-induced lung disease.     

Prediction of Genetic Values of Quantitative Traits in Plant Breeding Using Pedigree and Molecular Markers

The availability of dense molecular markers has made possible the use of genomic selection (GS) for plant breeding. However, the evaluation of models for GS in real plant populations is very limited. This article evaluates the performance of parametric and semiparametric models for GS using wheat (Triticum aestivum L.) and maize (Zea mays) data in which different traits were measured in several environmental conditions. The findings, based on extensive cross-validations, indicate that models including marker information had higher predictive ability than pedigree-based models. In the wheat data set, and relative to a pedigree model, gains in predictive ability due to inclusion of markers ranged from 7.7 to 35.7%. Correlation between observed and predictive values in the maize data set achieved values up to 0.79. Estimates of marker effects were different across environmental conditions, indicating that genotype × environment interaction is an important component of genetic variability. These results indicate that GS in plant breeding can be an effective strategy for selecting among lines whose phenotypes have yet to be observed.PEDIGREE-BASED prediction of genetic values based on the additive infinitesimal model (Fisher 1918) has played a central role in genetic improvement of complex traits in plants and animals. Animal breeders have used this model for predicting breeding values either in a mixed model (best linear unbiased prediction, BLUP) (Henderson 1984) or in a Bayesian framework (Gianola and Fernando 1986). More recently, plant breeders have incorporated pedigree information into linear mixed models for predicting breeding values (Crossa et al. 2006, 2007; Oakey et al. 2006; Burgueño et al. 2007; Piepho et al. 2007).The availability of thousands of genome-wide molecular markers has made possible the use of genomic selection (GS) for prediction of genetic values (Meuwissen et al. 2001) in plants (e.g., Bernardo and Yu 2007; Piepho 2009; Jannink et al. 2010) and animals (Gonzalez-Recio et al. 2008; VanRaden et al. 2008; Hayes et al. 2009; de los Campos et al. 2009a). Implementing GS poses several statistical and computational challenges, such as how models can cope with the curse of dimensionality, colinearity between markers, or the complexity of quantitative traits. Parametric (e.g., Meuwissen et al. 2001) and semiparametric (e.g., Gianola et al. 2006; Gianola and van Kaam 2008) methods address these problems differently.In standard genetic models, phenotypic outcomes, , are viewed as the sum of a genetic value, , and a model residual, ; that is, . In parametric models for GS, is described as a regression on marker covariates (j = 1,  …  , p molecular markers) of the form , such that(or , in matrix notation), where is the regression of on the jth marker covariate .Estimation of via multiple regression by ordinary least squares (OLS) is not feasible when p > n. A commonly used alternative is to estimate marker effects jointly using penalized methods such as ridge regression (Hoerl and Kennard 1970) or the Least Absolute Shrinkage and Selection Operator (LASSO) (Tibshirani 1996) or their Bayesian counterpart. This approach yields greater accuracy of estimated genetic values and can be coupled with geostatistical techniques commonly used in plant breeding to model multienvironments trials (Piepho 2009).In ridge regression (or its Bayesian counterpart) the extent of shrinkage is homogeneous across markers, which may not be appropriate if some markers are located in regions that are not associated with genetic variance, while markers in other regions may be linked to QTL (Goddard and Hayes 2007). To overcome this limitation, many authors have proposed methods that use marker-specific shrinkage. In a Bayesian setting, this can be implemented using priors of marker effects that are mixtures of scaled-normal densities. Examples of this are methods Bayes A and Bayes B of Meuwissen et al. (2001) and the Bayesian LASSO of Park and Casella (2008).An alternative to parametric regressions is to use semiparametric methods such as reproducing kernel Hilbert spaces (RKHS) regression (Gianola and van Kaam 2008). The Bayesian RKHS regression regards genetic values as random variables coming from a Gaussian process centered at zero and with a (co)variance structure that is proportional to a kernel matrix K (de los Campos et al. 2009b); that is, , where , are vectors of marker genotypes for the ith and jth individuals, respectively, and is a positive definite function evaluated in marker genotypes. In a finite-dimensional setting this amounts to modeling the vector of genetic values, , as multivariate normal; that is, where is a variance parameter. One of the most attractive features of RKHS regression is that the methodology can be used with almost any information set (e.g., covariates, strings, images, graphs). A second advantage is that with RKHS the model is represented in terms of n unknowns, which gives RKHS a great computational advantage relative to some parametric methods, especially when p ≫ n.This study presents an evaluation of several methods for GS, using two extensive data sets. One contains phenotypic records of a series of wheat trials and recently generated genomic data. The other data set pertains to international maize trials in which different traits were measured in maize lines evaluated under severe drought and well-watered conditions.     

Concomitant polymorphism: Crystallising dichloro-bis(2,4-lutidine)-zinc as both chiral and racemic phases

The crystallisation of dichloro-bis(2,4-lutidine)-zinc from various solvents (e.g. ethanol, THF and 2,4-lutidine) has been investigated and two phases were isolated. The structures of both phases were determined by single crystal X-ray diffraction and both types of crystals were found to be composed of conformationally chiral molecules. One phase (α-1) is racemic and crystallises in space group P2₁/c, while the other phase (β-1) crystallises in the enantiomorphous space group P4₁2₁2 with a low Flack parameter. In a few cases the chiral and racemic phases crystallised concomitantly; this phenomenon is rare and can be useful in the development of tools for the prediction of crystal structures.