Chemodiversity and molecular plasticity: recognition processes as explored by property spaces.

In the last few years, a need to account for molecular flexibility in drug-design methodologies has emerged, even if the dynamic behavior of molecular properties is seldom made explicit. For a flexible molecule, it is indeed possible to compute different values for a given conformation-dependent property and the ensemble of such values defines a property space that can be used to describe its molecular variability; a most representative case is the lipophilicity space. In this review, a number of applications of lipophilicity space and other property spaces are presented, showing that this concept can be fruitfully exploited: to investigate the constraints exerted by media of different levels of structural organization, to examine processes of molecular recognition and binding at an atomic level, to derive informative descriptors to be included in quantitative structure--activity relationships and to analyze protein simulations extracting the relevant information. Much molecular information is neglected in the descriptors used by medicinal chemists, while the concept of property space can fill this gap by accounting for the often-disregarded dynamic behavior of both small ligands and biomacromolecules. Property space also introduces some innovative concepts such as molecular sensitivity and plasticity, which appear best suited to explore the ability of a molecule to adapt itself to the environment variously modulating its property and conformational profiles. Globally, such concepts can enhance our understanding of biological phenomena providing fruitful descriptors in drug-design and pharmaceutical sciences.

Functional analysis of HLA-A*0201/Melan-A peptide multimer+ CD8+ T cells isolated from an HLA-A*0201- donor: exploring tumor antigen allorestricted recognition.

Recent studies in mouse models have suggested that genetic transfer of tumor antigen-specific high affinity T cell receptors (TCR) into host lymphocytes could be a viable strategy for the rapid induction of tumor-specific immunity. A previously proposed approach for the isolation of such TCRs consists in circumventing tolerance to self-restricting HLA/peptide complexes by deriving them from PMBCs of allogenic donors. Towards this aim, we used fluorescent HLA-A2 class-I/peptide soluble multimers to isolate A2-restricted CD8+ T cells specific for a previously described Melan-A peptide enhanced analog (Melan-A 26-35 A27L) from an HLA-A*0201 (A2) negative donor. We isolated two distinct groups of Melan-A 26-35 A27L-specific clones. Clones from the first group recognized the analog peptide with high avidity but showed very low recognition of Melan-A parental peptides. In contrast, clones from the second group efficiently recognized Melan-A parental peptides. Surprisingly however, most clones recognized not only A2+ Melan-A+ targets, but also A2+ Melan-A- targets suggesting that they can also recognize endogenous peptides other than Melan-A. In addition, one clone showed full cross-recognition of an antigenically unrelated peptide. Together, our data show that HLA-A2/peptide multimers can be successfully used for the isolation of allorestricted CD8+ T cells reactive with tumor antigen-derived peptides. However, as the cross-reactivity of these apparently peptide-specific allorestricted TCRs is presently unpredictable, a careful in vitro analysis of their reactivity to the host's normal cells is recommended.

Audit report on the Iowa Egg Council for the years ended June 30, 2013 and 2012

Audit report on the Iowa Egg Council for the years ended June 30, 2013 and 2012

Predicting the mating system from phenotypic correlations between life-history and sperm quality traits in the Alpine whitefish Coregonus zugensis

The mating behavior and reproductive strategies of Alpine whitefish like Coregonus zugensis (Nusslin) are poorly understood, probably because they spawn in deep water where direct observations are difficult. In this study, we interpret life-history and sperm quality traits of fish that we caught from their spawning place. We found that males invest heavily into gonadal tissue (up to 5.6% of their body weight), which is, in comparison to other fish, consistent with external fertilization, distinct pairing and moderate to high communal spawning, or no pairing and low to moderate communal spawning. Sperm competition theory and recent experimental studies on other salmonids predict that males optimize ejaculate characteristics in relation to the costs of sperm and the level of competition they have to expect: dominant males are predicted to invest less into ejaculate quality and to have slower spermatozoa than subdominant males. We found that spermatozoa of older males are slower than those of younger males. Moreover, older males have larger breeding tubercles, a secondary sexual trait that has, in some previous studies, been found to be linked to good condition and to good genetic quality. Our results suggest that C. zugensis has age-linked reproductive strategies, that multimale spawning is common, i.e., that sperm competition plays a significant role, and that older males are on average dominant over younger males at the spawning place.

Inter and intra-guild interactions in egg parasitoid species of the soybean stink bug complex

The objective of this research was to evaluate the parasitism behavior of Telenomus podisi Ashmead, Trissolcus basalis (Wollaston) e Trissolcus urichi Crawford (Hymenoptera: Scelionidae) on eggs of Nezara viridula L., Euschistus heros F., Piezodorus guildinii Westwood and Acrosternum aseadum Rolston (Heteroptera: Pentatomidae), in no choice and multiple choice experiments. For all parasitoid species, the results demonstrated the existence of a main host species that maximizes the reproductive success. The competitive interactions among the parasitoid species were investigated in experiments of sequential and simultaneous release of different combinations of parasitoid pairs on the hosts N. viridula, E. heros and A. aseadum. Exploitative competition was observed for egg batches at the genus level (Telenomus vs. Trissolcus) and interference competition at the species level (T. basalis vs. T. urichi). Trissolcus urichi was the most aggressive species, interfering with the parasitism of T. basalis. Generally, T. basalis showed an opportunistic behavior trying to parasitise eggs after T. urichi had abandoned the egg batch. The selection of parasitoid species for use in augmentative biological control programs should take into account the diversity of pentatomids present in soybean in addition to the interactions among the different species of parasitoids.

Prediction of cross-recognition of peptide-HLA A2 by Melan-A-specific cytotoxic T lymphocytes using three-dimensional quantitative structure-activity relationships.

The cross-recognition of peptides by cytotoxic T lymphocytes is a key element in immunology and in particular in peptide based immunotherapy. Here we develop three-dimensional (3D) quantitative structure-activity relationships (QSARs) to predict cross-recognition by Melan-A-specific cytotoxic T lymphocytes of peptides bound to HLA A*0201 (hereafter referred to as HLA A2). First, we predict the structure of a set of self- and pathogen-derived peptides bound to HLA A2 using a previously developed ab initio structure prediction approach [Fagerberg et al., J. Mol. Biol., 521-46 (2006)]. Second, shape and electrostatic energy calculations are performed on a 3D grid to produce similarity matrices which are combined with a genetic neural network method [So et al., J. Med. Chem., 4347-59 (1997)] to generate 3D-QSAR models. The models are extensively validated using several different approaches. During the model generation, the leave-one-out cross-validated correlation coefficient (q (2)) is used as the fitness criterion and all obtained models are evaluated based on their q (2) values. Moreover, the best model obtained for a partitioned data set is evaluated by its correlation coefficient (r = 0.92 for the external test set). The physical relevance of all models is tested using a functional dependence analysis and the robustness of the models obtained for the entire data set is confirmed using y-randomization. Finally, the validated models are tested for their utility in the setting of rational peptide design: their ability to discriminate between peptides that only contain side chain substitutions in a single secondary anchor position is evaluated. In addition, the predicted cross-recognition of the mono-substituted peptides is confirmed experimentally in chromium-release assays. These results underline the utility of 3D-QSARs in peptide mimetic design and suggest that the properties of the unbound epitope are sufficient to capture most of the information to determine the cross-recognition.

Insect eggs induce a systemic acquired resistance in Arabidopsis.

Although they constitute an inert stage of the insect's life, eggs trigger plant defences that lead to egg mortality or attraction of egg parasitoids. We recently found that salicylic acid (SA) accumulates in response to oviposition by the Large White butterfly Pieris brassicae, both in local and systemic leaves, and that plants activate a response that is similar to the recognition of pathogen-associated molecular patterns (PAMPs), which are involved in PAMP-triggered immunity (PTI). Here we discovered that natural oviposition by P. brassicae or treatment with egg extract inhibit growth of different Pseudomonas syringae strains in Arabidopsis through the activation of a systemic acquired resistance (SAR). This egg-induced SAR involves the metabolic SAR signal pipecolic acid, depends on ALD1 and FMO1, and is accompanied by a stronger induction of defence genes upon secondary infection. Although P. brassicae larvae showed a reduced performance when feeding on Pseudomonas syringae-infected plants, this effect was less pronounced when infected plants had been previously oviposited. Altogether, our results indicate that egg-induced SAR might have evolved as a strategy to prevent the detrimental effect of bacterial pathogens on feeding larvae.

Cytolytic T lymphocyte recognition of the murine cytomegalovirus nonstructural immediate-early protein pp89 expressed by recombinant vaccinia virus.

The murine immediate-early (IE) protein pp89 is a nonstructural virus-encoded phosphoprotein residing in the nucleus of infected cells, where it acts as transcriptional activator. Frequency analysis has shown that in BALB/c mice the majority of virus-specific CTL recognize IE antigens. The present study was performed to assess whether pp89 causes membrane antigen expression detected by IE-specific CTL. Site-directed mutagenesis has been used to delete the introns from gene ieI, encoding pp89, for subsequent integration of the continuous coding sequence into the vaccinia virus genome. After infection with the vaccinia recombinant, the authentic pp89 was expressed in cells that became susceptible to lysis by an IE-specific CTL clone. Priming of mice with the vaccinia recombinant sensitized polyclonal CTL that recognized MCMV-infected cells and transfected cells expressing pp89. Thus, a herpesviral IE polypeptide with essential function in viral transcriptional regulation can also serve as a dominant antigen for the specific CTL response of the host.

Recognition of major histoincompatibilities after transplantation with marrow from HLA closely matched donors.

BACKGROUND: To determine the extent to which major histoincompatibilities are recognized after bone marrow transplantation, we characterized the specificity of the cytotoxic T lymphocytes isolated during graft-versus-host disease. We studied three patients transplanted with marrow from donors who were histoincompatible for different types of HLA antigens. METHODS: Patient 1 was mismatched for one "ABDR-antigen" (HLA-A2 versus A3). Two patients were mismatched for antigens that would usually not be taken into account by standard selection procedures: patient 2 was mismatched for an "HLA-A subtype" (A*0213 versus A*0201), whereas patient 3 was mismatched for HLA-C (HLA-C*0501 versus HLA-C*0701). All three HLA class I mismatches were detected by a pretransplant cytotoxic precursor test. RESULTS: Analysis of the specificity of the cytotoxic T lymphocyte clones isolated after transplantation showed that the incompatibilities detected by the pretransplant cytotoxic precursor assay were the targets recognized during graft-versus-host disease. CONCLUSIONS: Independent of whether the incompatibility consisted of a "full" mismatch, a "subtype" mismatch, or an HLA-C mismatch, all clones recognized the incompatible HLA molecule. In addition, some of these clones had undergone antigen selection and were clearly of higher specificity than the ones established before transplantation, indicating that they had been participating directly in the antihost immune response.

Low TCR avidity and lack of tumor cell recognition in CD8(+) T cells primed with the CEA-analogue CAP1-6D peptide.

The use of "altered peptide ligands" (APL), epitopes designed for exerting increased immunogenicity as compared with native determinants, represents nowadays one of the most utilized strategies for overcoming immune tolerance to self-antigens and boosting anti-tumor T cell-mediated immune responses. However, the actual ability of APL-primed T cells to cross-recognize natural epitopes expressed by tumor cells remains a crucial concern. In the present study, we show that CAP1-6D, a superagonist analogue of a carcinoembriyonic antigen (CEA)-derived HLA-A*0201-restricted epitope widely used in clinical setting, reproducibly promotes the generation of low-affinity CD8(+) T cells lacking the ability to recognized CEA-expressing colorectal carcinoma (CRC) cells. Short-term T cell cultures, obtained by priming peripheral blood mononuclear cells from HLA-A*0201(+) healthy donors or CRC patients with CAP1-6D, were indeed found to heterogeneously cross-react with saturating concentrations of the native peptide CAP1, but to fail constantly lysing or recognizing through IFN- gamma release CEA(+)CRC cells. Characterization of anti-CAP1-6D T cell avidity, gained through peptide titration, CD8-dependency assay, and staining with mutated tetramers (D227K/T228A), revealed that anti-CAP1-6D T cells exerted a differential interaction with the two CEA epitopes, i.e., displaying high affinity/CD8-independency toward the APL and low affinity/CD8-dependency toward the native CAP1 peptide. Our data demonstrate that the efficient detection of self-antigen expressed by tumors could be a feature of high avidity CD8-independent T cells, and underline the need for extensive analysis of tumor cross-recognition prior to any clinical usage of APL as anti-cancer vaccines.

Maximum likelihood Linear Programming Data Fusion for Speaker Recognition

Biometric system performance can be improved by means of data fusion. Several kinds of information can be fused in order to obtain a more accurate classification (identification or verification) of an input sample. In this paper we present a method for computing the weights in a weighted sum fusion for score combinations, by means of a likelihood model. The maximum likelihood estimation is set as a linear programming problem. The scores are derived from a GMM classifier working on a different feature extractor. Our experimental results assesed the robustness of the system in front a changes on time (different sessions) and robustness in front a change of microphone. The improvements obtained were significantly better (error bars of two standard deviations) than a uniform weighted sum or a uniform weighted product or the best single classifier. The proposed method scales computationaly with the number of scores to be fussioned as the simplex method for linear programming.

Application of the Mutual Information Minimization to speaker recognition / identification improvement

In this paper we propose the inversion of nonlinear distortions in order to improve the recognition rates of a speaker recognizer system. We study the effect of saturations on the test signals, trying to take into account real situations where the training material has been recorded in a controlled situation but the testing signals present some mismatch with the input signal level (saturations). The experimental results for speaker recognition shows that a combination of several strategies can improve the recognition rates with saturated test sentences from 80% to 89.39%, while the results with clean speech (without saturation) is 87.76% for one microphone, and for speaker identification can reduce the minimum detection cost function with saturated test sentences from 6.42% to 4.15%, while the results with clean speech (without saturation) is 5.74% for one microphone and 7.02% for the other one.

Improving a leaves automatic recognition process using PCA

In this work we present a simulation of a recognition process with perimeter characterization of a simple plant leaves as a unique discriminating parameter. Data coding allowing for independence of leaves size and orientation may penalize performance recognition for some varieties. Border description sequences are then used, and Principal Component Analysis (PCA) is applied in order to study which is the best number of components for the classification task, implemented by means of a Support Vector Machine (SVM) System. Obtained results are satisfactory, and compared with [4] our system improves the recognition success, diminishing the variance at the same time.

Automatic Recognition of Leaves by Shape Detection Pre-Processing with Ica

In this work we present a simulation of a recognition process with perimeter characterization of a simple plant leaves as a unique discriminating parameter. Data coding allowing for independence of leaves size and orientation may penalize performance recognition for some varieties. Border description sequences are then used to characterize the leaves. Independent Component Analysis (ICA) is then applied in order to study which is the best number of components to be considered for the classification task, implemented by means of an Artificial Neural Network (ANN). Obtained results with ICA as a pre-processing tool are satisfactory, and compared with some references our system improves the recognition success up to 80.8% depending on the number of considered independent components.

Empirical mode decomposition-based face recognition system

In this work we explore the multivariate empirical mode decomposition combined with a Neural Network classifier as technique for face recognition tasks. Images are simultaneously decomposed by means of EMD and then the distance between the modes of the image and the modes of the representative image of each class is calculated using three different distance measures. Then, a neural network is trained using 10- fold cross validation in order to derive a classifier. Preliminary results (over 98 % of classification rate) are satisfactory and will justify a deep investigation on how to apply mEMD for face recognition.