Evaluation of the genetic trend of milk yield in the multiple ovulation and embryo transfer populations of dairy cows, using stochastic simulation

Stochastic modeling of dairy cattle populations using multiple ovulation and embryo transfer (MOET) was used to compare 15-year genetic responses with an artificial insemination (AI) program. MOET and AI techniques were simulated in four populations, two with 100 breeding females each and two with 400 breeding females. The selection goal was to maximize genetic progress in milk yield. The reduction in genetic variation due to inbreeding and linkage disequilibrium was accounted for in the simulation process. All four MOET breeding schemes studied achieved larger genetic responses than the realized and theoretical genetic gains from the current AI progeny testing populations. Strict restriction against inbred matings slowed genetic progress significantly in the small population but would not be consequential in the larger population. However, allowing inbred matings in the smaller population caused a rapid accumulation of inbreeding. Linkage disequilibrium was as important as inbreeding in reducing genetic variation. Genetic drift variance was much smaller in the larger population.     

Thermal stability of the human immunodeficiency virus type 1 (HIV-1) receptors, CD4 and CXCR4, reconstituted in proteoliposomes

Background

The entry of human immunodeficiency virus (HIV-1) into host cells involves the interaction of the viral exterior envelope glycoprotein, gp120, and receptors on the target cell. The HIV-1 receptors are CD4 and one of two chemokine receptors, CCR5 or CXCR4.

Methodology/Principal Findings

We created proteoliposomes that contain CD4, the primary HIV-1 receptor, and one of the coreceptors, CXCR4. Antibodies against CD4 and CXCR4 specifically bound the proteoliposomes. CXCL12, the natural ligand for CXCR4, and the small-molecule CXCR4 antagonist, AMD3100, bound the proteoliposomes with affinities close to those associated with the binding of these molecules to cells expressing CXCR4 and CD4. The HIV-1 gp120 exterior envelope glycoprotein bound tightly to proteoliposomes expressing only CD4 and, in the presence of soluble CD4, bound weakly to proteoliposomes expressing only CXCR4. The thermal stability of CD4 and CXCR4 inserted into liposomes was examined. Thermal denaturation of CXCR4 followed second-order kinetics, with an activation energy (E_a) of 269 kJ/mol (64.3 kcal/mol) and an inactivation temperature (T_i) of 56°C. Thermal inactivation of CD4 exhibited a reaction order of 1.3, an E_a of 278 kJ/mol (66.5 kcal/mol), and a T_i of 52.2°C. The second-order denaturation kinetics of CXCR4 is unusual among G protein-coupled receptors, and may result from dimeric interactions between CXCR4 molecules.

Conclusions/Significance

Our studies with proteoliposomes containing the native HIV-1 receptors allowed an examination of the binding of biologically important ligands and revealed the higher-order denaturation kinetics of these receptors. CD4/CXCR4-proteoliposomes may be useful for the study of virus-target cell interactions and for the identification of inhibitors.     

Impact of mutations in the coreceptor binding site on human immunodeficiency virus type 1 fusion, infection, and entry inhibitor sensitivity

An increasingly large number of antiviral agents that prevent entry of human immunodeficiency virus (HIV) into cells are in preclinical and clinical development. The envelope (Env) protein of HIV is the major viral determinant that affects sensitivity to these compounds. To understand how changes in Env can impact entry inhibitor sensitivity, we introduced six mutations into the conserved coreceptor binding site of the R5 HIV-1 strain YU-2 and measured the effect of these changes on CD4 and coreceptor binding, membrane fusion levels and rates, virus infection, and sensitivity to the fusion inhibitors enfuvirtide (T-20) and T-1249, the CCR5 inhibitor TAK-779, and an antibody to CD4. The mutations had little effect on CD4 binding but reduced CCR5 binding to various extents. In general, reductions in coreceptor binding efficiency resulted in slower fusion kinetics and increased sensitivity to TAK-779 and enfuvirtide. In addition, low CCR5 binding usually reduced overall fusion and infection levels. However, one mutation adjacent to the bridging sheet beta21 strand, P438A, had little effect on fusion activity, fusion rate, infectivity, or sensitivity to enfuvirtide or T-1249 despite causing a marked reduction in CCR5 binding and a significant increase in TAK-779 sensitivity. Thus, our findings indicate that changes in the coreceptor binding site of Env can modulate its fusion activity, infectivity, and entry inhibitor sensitivity by multiple mechanisms and suggest that reductions in coreceptor binding do not always result in prolonged fusion kinetics and increased sensitivity to enfuvirtide.     

Determining the Most Important Physiological and Agronomic Traits Contributing to Maize Grain Yield through Machine Learning Algorithms: A New Avenue in Intelligent Agriculture

Prediction is an attempt to accurately forecast the outcome of a specific situation while using input information obtained from a set of variables that potentially describe the situation. They can be used to project physiological and agronomic processes; regarding this fact, agronomic traits such as yield can be affected by a large number of variables. In this study, we analyzed a large number of physiological and agronomic traits by screening, clustering, and decision tree models to select the most relevant factors for the prospect of accurately increasing maize grain yield. Decision tree models (with nearly the same performance evaluation) were the most useful tools in understanding the underlying relationships in physiological and agronomic features for selecting the most important and relevant traits (sowing date-location, kernel number per ear, maximum water content, kernel weight, and season duration) corresponding to the maize grain yield. In particular, decision tree generated by C&RT algorithm was the best model for yield prediction based on physiological and agronomical traits which can be extensively employed in future breeding programs. No significant differences in the decision tree models were found when feature selection filtering on data were used, but positive feature selection effect observed in clustering models. Finally, the results showed that the proposed model techniques are useful tools for crop physiologists to search through large datasets seeking patterns for the physiological and agronomic factors, and may assist the selection of the most important traits for the individual site and field. In particular, decision tree models are method of choice with the capability of illustrating different pathways of yield increase in breeding programs, governed by their hierarchy structure of feature ranking as well as pattern discovery via various combinations of features.     

Experimental Analysis of E2BB (LTIIb) Signal Peptide in Secretory Production of Reteplase in Escherichia coli

International Journal of Peptide Research and Therapeutics - Recombinant reteplase is the truncated form of tissue plasminogen activator. Signal peptides play a pivotal role in the secretion of...     

Contribution of intrinsic reactivity of the HIV-1 envelope glycoproteins to CD4-independent infection and global inhibitor sensitivity

Human immunodeficiency virus (HIV-1) enters cells following sequential activation of the high-potential-energy viral envelope glycoprotein trimer by target cell CD4 and coreceptor. HIV-1 variants differ in their requirements for CD4; viruses that can infect coreceptor-expressing cells that lack CD4 have been generated in the laboratory. These CD4-independent HIV-1 variants are sensitive to neutralization by multiple antibodies that recognize different envelope glycoprotein epitopes. The mechanisms underlying CD4 independence, global sensitivity to neutralization and the association between them are still unclear. By studying HIV-1 variants that differ in requirements for CD4, we investigated the contribution of CD4 binding to virus entry. CD4 engagement exposes the coreceptor-binding site and increases the "intrinsic reactivity" of the envelope glycoproteins; intrinsic reactivity describes the propensity of the envelope glycoproteins to negotiate transitions to lower-energy states upon stimulation. Coreceptor-binding site exposure and increased intrinsic reactivity promote formation/exposure of the HR1 coiled coil on the gp41 transmembrane glycoprotein and allow virus entry upon coreceptor binding. Intrinsic reactivity also dictates the global sensitivity of HIV-1 to perturbations such as exposure to cold and the binding of antibodies and small molecules. Accordingly, CD4 independence of HIV-1 was accompanied by increased susceptibility to inactivation by these factors. We investigated the role of intrinsic reactivity in determining the sensitivity of primary HIV-1 isolates to inhibition. Relative to the more common neutralization-resistant ("Tier 2-like") viruses, globally sensitive ("Tier 1") viruses exhibited increased intrinsic reactivity, i.e., were inactivated more efficiently by cold exposure or by a given level of antibody binding to the envelope glycoprotein trimer. Virus sensitivity to neutralization was dictated both by the efficiency of inhibitor/antibody binding to the envelope glycoprotein trimer and by envelope glycoprotein reactivity to the inhibitor/antibody binding event. Quantitative differences in intrinsic reactivity contribute to HIV-1 strain variability in global susceptibility to neutralization and explain the long-observed relationship between increased inhibitor sensitivity and decreased entry requirements for target cell CD4.     

Genetic relationship between milk urea nitrogen and reproductive performance in Holstein dairy cows

The objective of this study was to describe the genetic and phenotypic relationship between milk urea nitrogen (MUN) and reproductive traits in Iranian Holstein dairy cows. Test-day MUN data obtained from 57 301 dairy cows on 20 large dairy herds in Iran between January 2005 and June 2009. Genetic parameters for MUN and reproductive traits were estimated with a five-trait model using ASREML program. Random regression test-day models were used to estimate heritabilities separately for MUN from first, second and third lactations. Regression curves were modeled using Legendre polynomials of order 3. Herd-year-season along with age at calving was included as fixed effects in all models for reproductive traits. Heritabilities for MUN and reproductive traits were estimated separately for first lactation, second lactation and third lactation. The estimated heritabilities for MUN varied from 0.18 to 0.22. The heritability estimate was low for reproductive traits, which ranged from 0.02 to 0.06 for different traits and across parities. Except for days open, phenotypic and genetic correlations of MUN with reproductive performance traits were close to zero. Genetic correlations between MUN and days open were 0.23, 0.35 and 0.45 in first, second and third lactation, respectively. However, the phenotypic correlation between MUN at different parities was moderate (0.28 to 0.35), but the genetic correlation between MUN at different parities was high and ranged from 0.84 to 0.97. This study shows a limited application of MUN for use in selection programs to improve reproductive performance.