Select gp120 V2 domain specific antibodies derived from HIV and SIV infection and vaccination inhibit gp120 binding to alpha4beta7

The GI tract is preferentially targeted during acute/early HIV-1 infection. Consequent damage to the gut plays a central role in HIV pathogenesis. The basis for preferential targeting of gut tissues is not well defined. Recombinant proteins and synthetic peptides derived from HIV and SIV gp120 bind directly to integrin alpha4beta7, a gut-homing receptor. Using both cell-surface expressed alpha4beta7 and a soluble alpha4beta7 heterodimer we demonstrate that its specific affinity for gp120 is similar to its affinity for MAdCAM (its natural ligand). The gp120 V2 domain preferentially engages extended forms of alpha4beta7 in a cation -sensitive manner and is inhibited by soluble MAdCAM. Thus, V2 mimics MAdCAM in the way that it binds to alpha4beta7, providing HIV a potential mechanism to discriminate between functionally distinct subsets of lymphocytes, including those with gut-homing potential. Furthermore, alpha4beta7 antagonists developed for the treatment of inflammatory bowel diseases, block V2 binding to alpha4beta7. A 15-amino acid V2 -derived peptide is sufficient to mediate binding to alpha4beta7. It includes the canonical LDV/I alpha4beta7 binding site, a cryptic epitope that lies 7-9 amino acids amino terminal to the LDV/I, and residues K169 and I181. These two residues were identified in a sieve analysis of the RV144 vaccine trial as sites of vaccine -mediated immune pressure. HIV and SIV V2 mAbs elicited by both vaccination and infection that recognize this peptide block V2-alpha4beta7 interactions. These mAbs recognize conformations absent from the beta- barrel presented in a stabilized HIV SOSIP gp120/41 trimer. The mimicry of MAdCAM-alpha4beta7 interactions by V2 may influence early events in HIV infection, particularly the rapid seeding of gut tissues, and supports the view that HIV replication in gut tissue is a central feature of HIV pathogenesis

Seven new dolphin mitochondrial genomes and a time-calibrated phylogeny of whales

<p>Abstract</p> <p>Background</p> <p>The phylogeny of Cetacea (whales) is not fully resolved with substantial support. The ambiguous and conflicting results of multiple phylogenetic studies may be the result of the use of too little data, phylogenetic methods that do not adequately capture the complex nature of DNA evolution, or both. In addition, there is also evidence that the generic taxonomy of Delphinidae (dolphins) underestimates its diversity. To remedy these problems, we sequenced the complete mitochondrial genomes of seven dolphins and analyzed these data with partitioned Bayesian analyses. Moreover, we incorporate a newly-developed "relaxed" molecular clock to model heterogenous rates of evolution among cetacean lineages.</p> <p>Results</p> <p>The "deep" phylogenetic relationships are well supported including the monophyly of Cetacea and Odontoceti. However, there is ambiguity in the phylogenetic affinities of two of the river dolphin clades Platanistidae (Indian River dolphins) and Lipotidae (Yangtze River dolphins). The phylogenetic analyses support a sister relationship between Delphinidae and Monodontidae + Phocoenidae. Additionally, there is statistically significant support for the paraphyly of <it>Tursiops </it>(bottlenose dolphins) and <it>Stenella </it>(spotted dolphins).</p> <p>Conclusion</p> <p>Our phylogenetic analysis of complete mitochondrial genomes using recently developed models of rate autocorrelation resolved the phylogenetic relationships of the major Cetacean lineages with a high degree of confidence. Our results indicate that a rapid radiation of lineages explains the lack of support the placement of Platanistidae and Lipotidae. Moreover, our estimation of molecular divergence dates indicates that these radiations occurred in the Middle to Late Oligocene and Middle Miocene, respectively. Furthermore, by collecting and analyzing seven new mitochondrial genomes, we provide strong evidence that the delphinid genera <it>Tursiops </it>and <it>Stenella </it>are not monophyletic, and the current taxonomy masks potentially interesting patterns of morphological, physiological, behavioral, and ecological evolution.</p

Considerable MHC Diversity Suggests That the Functional Extinction of Baiji Is Not Related to Population Genetic Collapse

To further extend our understanding of the mechanism causing the current nearly extinct status of the baiji (Lipotes vexillifer), one of the most critically endangered species in the world, genetic diversity at the major histocompatibility complex (MHC) class II DRB locus was investigated in the baiji. Nine highly divergent DRB alleles were identified in 17 samples, with an average of 28.4 (13.2%) nucleotide difference and 16.7 (23.5%) amino acid difference between alleles. The unexpectedly high levels of DRB allelic diversity in the baiji may partly be attributable to its evolutionary adaptations to the freshwater environment which is regarded to have a higher parasite diversity compared to the marine environment. In addition, balancing selection was found to be the main mechanisms in generating sequence diversity at baiji DRB gene. Considerable sequence variation at the adaptive MHC genes despite of significant loss of neutral genetic variation in baiji genome might suggest that intense selection has overpowered random genetic drift as the main evolutionary forces, which further suggested that the critically endangered or nearly extinct status of the baiji is not an outcome of genetic collapse

Adaptive evolution and functional constraint at TLR4 during the secondary aquatic adaptation and diversification of cetaceans

<p>Abstract</p> <p>Background</p> <p>Cetaceans (whales, dolphins and porpoises) are a group of adapted marine mammals with an enigmatic history of transition from terrestrial to full aquatic habitat and rapid radiation in waters around the world. Throughout this evolution, the pathogen stress-response proteins must have faced challenges from the dramatic change of environmental pathogens in the completely different ecological niches cetaceans occupied. For this reason, cetaceans could be one of the most ideal candidate taxa for studying evolutionary process and associated driving mechanism of vertebrate innate immune systems such as Toll-like receptors (TLRs), which are located at the direct interface between the host and the microbial environment, act at the first line in recognizing specific conserved components of microorganisms, and translate them rapidly into a defense reaction.</p> <p>Results</p> <p>We used TLR4 as an example to test whether this traditionally regarded pattern recognition receptor molecule was driven by positive selection across cetacean evolutionary history. Overall, the lineage-specific selection test showed that the <it>dN/dS </it>(ω) values along most (30 out of 33) examined cetartiodactylan lineages were less than 1, suggesting a common effect of functional constraint. However, some specific codons made radical changes, fell adjacent to the residues interacting with lipopolysaccharides (LPS), and showed parallel evolution between independent lineages, suggesting that TLR4 was under positive selection. Especially, strong signatures of adaptive evolution on TLR4 were identified in two periods, one corresponding to the early evolutionary transition of the terrestrial ancestors of cetaceans from land to semi-aquatic (represented by the branch leading to whale + hippo) and from semi-aquatic to full aquatic (represented by the ancestral branch leading to cetaceans) habitat, and the other to the rapid diversification and radiation of oceanic dolphins.</p> <p>Conclusions</p> <p>This is the first study thus far to characterize the TLR gene in cetaceans. Our data present evidences that cetacean TLR4 has undergone adaptive evolution against the background of purifying selection in response to the secondary aquatic adaptation and rapid diversification in the sea. It is suggested that microbial pathogens in different environments are important factors that promote adaptive changes at cetacean TLR4 and new functions of some amino acid sites specialized for recognizing pathogens in dramatically contrasted environments to enhance the fitness for the adaptation and survival of cetaceans.</p

The loss of taste genes in cetaceans

Background: Five basic taste modalities, sour, sweet, bitter, salt and umami, can be distinguished by humans and are fundamental for physical and ecological adaptations in mammals. Molecular genetic studies of the receptor genes for these tastes have been conducted in terrestrial mammals; however, little is known about the evolution and adaptation of these genes in marine mammals. Results: Here, all five basic taste modalities, sour, sweet, bitter, salt and umami, were investigated in cetaceans. The sequence characteristics and evolutionary analyses of taste receptor genes suggested that nearly all cetaceans may have lost all taste modalities except for that of salt. Conclusions: This is the first study to comprehensively examine the five basic taste modalities in cetaceans with extensive taxa sampling. Our results suggest that cetaceans have lost four of the basic taste modalities including sour, sweet, umami, and most of the ability to sense bitter tastes. The integrity of the candidate salt taste receptor genes in all the cetaceans examined may be because of their function in Na+ reabsorption, which is key to osmoregulation and aquatic adaptation. Electronic supplementary material The online version of this article (doi:10.1186/s12862-014-0218-8) contains supplementary material, which is available to authorized users

User-friendly optimization approach of fed-batch fermentation conditions for the production of iturin A using artificial neural networks and support vector machine

Background: In the field of microbial fermentation technology, how to optimize the fermentation conditions is of great crucial for practical applications. Here, we use artificial neural networks (ANNs) and support vector machine (SVM) to offer a series of effective optimization methods for the production of iturin A. The concentration levels of asparagine (Asn), glutamic acid (Glu) and proline (Pro) (mg/L) were set as independent variables, while the iturin A titer (U/mL) was set as dependent variable. General regression neural network (GRNN), multilayer feed-forward neural networks (MLFNs) and the SVM were developed. Comparisons were made among different ANNs and the SVM. Results: The GRNN has the lowest RMS error (457.88) and the shortest training time (1 s), with a steady fluctuation during repeated experiments, whereas the MLFNs have comparatively higher RMS errors and longer training times, which have a significant fluctuation with the change of nodes. In terms of the SVM, it also has a relatively low RMS error (466.13), with a short training time (1 s). Conclusion: According to the modeling results, the GRNN is considered as the most suitable ANN model for the design of the fed-batch fermentation conditions for the production of iturin A because of its high robustness and precision, and the SVM is also considered as a very suitable alternative model. Under the tolerance of 30%, the prediction accuracies of the GRNN and SVM are both 100% respectively in repeated experiments

Interactive correction of mislabeled training data

In this paper, we develop a visual analysis method for interactively improving the quality of labeled data, which is essential to the success of supervised and semi-supervised learning. The quality improvement is achieved through the use of user-selected trusted items. We employ a bi-level optimization model to accurately match the labels of the trusted items and to minimize the training loss. Based on this model, a scalable data correction algorithm is developed to handle tens of thousands of labeled data efficiently. The selection of the trusted items is facilitated by an incremental tSNE with improved computational efficiency and layout stability to ensure a smooth transition between different levels. We evaluated our method on real-world datasets through quantitative evaluation and case studies, and the results were generally favorable

Interactive correction of mislabeled training data

In this paper, we develop a visual analysis method for interactively improving the quality of labeled data, which is essential to the success of supervised and semi-supervised learning. The quality improvement is achieved through the use of user-selected trusted items. We employ a bi-level optimization model to accurately match the labels of the trusted items and to minimize the training loss. Based on this model, a scalable data correction algorithm is developed to handle tens of thousands of labeled data efficiently. The selection of the trusted items is facilitated by an incremental tSNE with improved computational efficiency and layout stability to ensure a smooth transition between different levels. We evaluated our method on real-world datasets through quantitative evaluation and case studies, and the results were generally favorable