Recognition of a defined region within p24 gag by CD8+ T cells during primary human immunodeficiency virus type 1 infection in individuals expressing protective HLA class I alleles

Human immunodeficiency virus type 1 (HIV-1)-specific immune responses during primary HIV-1 infection appear to play a critical role in determining the ultimate speed of disease progression, but little is known about the specificity of the initial HIV-1-specific CD8(+) T-cell responses in individuals expressing protective HLA class I alleles. Here we compared HIV-1-specific T-cell responses between subjects expressing the protective allele HLA-B27 or -B57 and subjects expressing nonprotective HLA alleles using a cohort of over 290 subjects identified during primary HIV-1 infection. CD8(+) T cells of individuals expressing HLA-B27 or -B57 targeted a defined region within HIV-1 p24 Gag (amino acids 240 to 272) early in infection, and responses against this region contributed over 35% to the total HIV-1-specific T-cell responses in these individuals. In contrast, this region was rarely recognized in individuals expressing HLA-B35, an HLA allele associated with rapid disease progression, or in subjects expressing neither HLA-B57/B27 nor HLA-B35 (P < 0.0001). The identification of this highly conserved region in p24 Gag targeted in primary infection specifically in individuals expressing HLA class I alleles associated with slower HIV-1 disease progression provides a rationale for vaccine design aimed at inducing responses to this region restricted by other, more common HLA class I alleles.     

Phage display for engineering and analyzing protein interaction interfaces

Phage display is the longest-standing platform among molecular display technologies. Recent developments have extended its utility to proteins that were previously recalcitrant to phage display. The technique has played a dominant role in forming the field of synthetic binding protein engineering, where novel interfaces have been generated from libraries built using antibody fragment frameworks and also alternative scaffolds. Combinatorial methods have also been developed for the rapid analysis of binding energetics across protein interfaces. The ability to rapidly select and analyze binding interfaces, and compatibility with high-throughput methods under diverse conditions, makes it likely that the combination of phage display and synthetic combinatorial libraries will prove to be the method of choice for synthetic binding protein engineering for broad applications.     

Biotin- and Glycoprotein-Coated Microspheres as Surrogates for Studying Filtration Removal of Cryptosporidium parvum in a Granular Limestone Aquifer Medium

Members of the genus Cryptosporidium are waterborne protozoa of great health concern. Many studies have attempted to find appropriate surrogates for assessing Cryptosporidium filtration removal in porous media. In this study, we evaluated the filtration of Cryptosporidium parvum in granular limestone medium by the use of biotin- and glycoprotein-coated carboxylated polystyrene microspheres (CPMs) as surrogates. Column experiments were carried out with core material taken from a managed aquifer recharge site in Adelaide, Australia. For the experiments with injection of a single type of particle, we observed the total removal of the oocysts and glycoprotein-coated CPMs, a 4.6- to 6.3-log₁₀ reduction of biotin-coated CPMs, and a 2.6-log₁₀ reduction of unmodified CPMs. When two different types of particles were simultaneously injected, glycoprotein-coated CPMs showed a 5.3-log₁₀ reduction, while the uncoated CPMs displayed a 3.7-log₁₀ reduction, probably due to particle-particle interactions. Our results confirm that glycoprotein-coated CPMs are the most accurate surrogates for C. parvum; biotin-coated CPMs are slightly more conservative, while unmodified CPMs are markedly overly conservative for predicting C. parvum removal in granular limestone medium. The total removal of C. parvum observed in our study suggests that granular limestone medium is very effective for the filtration removal of C. parvum and could potentially be used for the pretreatment of drinking water and aquifer storage recovery of recycled water.     

3-Thio-1,2,4-triazoles, novel somatostatin sst2/sst5 agonists

Novel 3-thio-1,2,4-triazoles have been obtained via a solution-phase parallel synthesis strategy, affording potent non-peptidic human somatostatin receptor subtypes 2 and 5 agonists.     

Definition of the consensus motif recognized by gamma-adaptin ear domains

The heterotetrameric adaptor complex 1 (AP-1) and the monomeric Golgi-localized, gamma ear-containing, Arf-binding (GGA) proteins are components of clathrin coats associated with the trans-Golgi network and endosomes. The carboxyl-terminal ear domains (or gamma-adaptin ear (GAE) domains) of two gamma-adaptin subunit isoforms of AP-1 and of the GGAs are structurally similar and bind to a common set of accessory proteins. In this study, we have systematically defined a core tetrapeptide motif PsiG(P/D/E)(Psi/L/M) (where Psi is an aromatic residue), which is responsible for the interactions of accessory proteins with GAE domains. The definition of this motif has allowed us to identify novel GAE-binding partners named NECAP and aftiphilin, which also contain clathrin-binding motifs. These findings shed light on the mechanism of accessory protein recruitment to trans-Golgi network and endosomal clathrin coats.     

Prediction of Signal Peptides Using Bio-Basis Function Neural Networks and Decision Trees

Signal peptide identification is of immense importance in drug design. Accurate identification of signal peptides is the first critical step to be able to change the direction of the targeting proteins and use the designed drug to target a specific organelle to correct a defect. Because experimental identification is the most accurate method, but is expensive and time-consuming, an efficient and affordable automated system is of great interest. In this article, we propose using an adapted neural network, called a bio-basis function neural network, and decision trees for predicting signal peptides. The bio-basis function neural network model and decision trees achieved 97.16% and 97.63% accuracy respectively, demonstrating that the methods work well for the prediction of signal peptides. Moreover, decision trees revealed that position P(1'), which is important in forming signal peptides, most commonly comprises either leucine or alanine. This concurs with the (P(3)-P(1)-P(1')) coupling model.     

A dye binding method for measurement of total protein in microalgae

Protein is a large component of the standing biomass of algae. The total protein content of algae is difficult to measure because of the problems encountered in extracting all of the protein from the cells. Here we modified an existing protein assay to measure total protein in microalgae cells that involves little or no extraction of protein from the cells. Aliquots of fresh or pretreated cells were spotted onto filter paper strips. After drying, the strips were stained in a 0.1% (w/v) solution of the protein stain Coomassie Brilliant Blue R-250 for 16 to 24 h and then destained. The stained protein spots were cut out from the paper, and dye was eluted in 1% (w/v) sodium dodecyl sulfate (SDS). Absorbance at 600 nm was directly proportional to protein concentration. Cells that were recalcitrant to taking up the dye could be either heated at 80°C for 10 min in 1% SDS or briefly sonicated for 3 min to facilitate penetration of the dye into the cells. Total protein measured in Chlorella vulgaris using this method compared closely with that measured using the total N method. Total protein concentrations were measured successfully in 12 algal species using this dye binding method.