Comparison of HIV-1 Genotypic Resistance Test Interpretation Systems in Predicting Virological Outcomes Over Time

Background

Several decision support systems have been developed to interpret HIV-1 drug resistance genotyping results. This study compares the ability of the most commonly used systems (ANRS, Rega, and Stanford''s HIVdb) to predict virological outcome at 12, 24, and 48 weeks.

Methodology/Principal Findings

Included were 3763 treatment-change episodes (TCEs) for which a HIV-1 genotype was available at the time of changing treatment with at least one follow-up viral load measurement. Genotypic susceptibility scores for the active regimens were calculated using scores defined by each interpretation system. Using logistic regression, we determined the association between the genotypic susceptibility score and proportion of TCEs having an undetectable viral load (<50 copies/ml) at 12 (8–16) weeks (2152 TCEs), 24 (16–32) weeks (2570 TCEs), and 48 (44–52) weeks (1083 TCEs). The Area under the ROC curve was calculated using a 10-fold cross-validation to compare the different interpretation systems regarding the sensitivity and specificity for predicting undetectable viral load. The mean genotypic susceptibility score of the systems was slightly smaller for HIVdb, with 1.92±1.17, compared to Rega and ANRS, with 2.22±1.09 and 2.23±1.05, respectively. However, similar odds ratio''s were found for the association between each-unit increase in genotypic susceptibility score and undetectable viral load at week 12; 1.6 [95% confidence interval 1.5–1.7] for HIVdb, 1.7 [1.5–1.8] for ANRS, and 1.7 [1.9–1.6] for Rega. Odds ratio''s increased over time, but remained comparable (odds ratio''s ranging between 1.9–2.1 at 24 weeks and 1.9–2.2 at 48 weeks). The Area under the curve of the ROC did not differ between the systems at all time points; p = 0.60 at week 12, p = 0.71 at week 24, and p = 0.97 at week 48.

Conclusions/Significance

Three commonly used HIV drug resistance interpretation systems ANRS, Rega and HIVdb predict virological response at 12, 24, and 48 weeks, after change of treatment to the same extent.     

Non-hematopoietic cells in lymph nodes drive memory CD8 T cell inflation during murine cytomegalovirus infection

During human and murine cytomegalovirus (MCMV) infection an exceptionally large virus-specific CD8 T cell pool is maintained in the periphery lifelong. This anomalous response is only seen for specific subsets of MCMV-specific CD8 T cells which are referred to as 'inflationary T cells'. How memory CD8 T cell inflation is induced and maintained is unclear, though their activated phenotype strongly suggests an involvement of persistent antigen encounter during MCMV latency. To dissect the cellular and molecular requirements for memory CD8 T cell inflation, we have generated a transgenic mouse expressing an MHC class I-restricted T cell receptor specific for an immunodominant inflationary epitope of MCMV. Through a series of adoptive transfer experiments we found that memory inflation was completely dependent on antigen presentation by non-hematopoietic cells, which are also the predominant site of MCMV latency. In particular, non-hematopoietic cells selectively induced robust proliferation of inflationary CD8 T cells in lymph nodes, where a majority of the inflationary CD8 T cells exhibit a central-memory phenotype, but not in peripheral tissues, where terminally differentiated inflationary T cells accumulate. These results indicate that continuous restimulation of central memory CD8 T cells in the lymph nodes by infected non-hematopoietic cells ensures the maintenance of a functional effector CD8 T pool in the periphery, providing protection against viral reactivation events.     

Bioinformatics tools for cancer metabolomics

It is well known that significant metabolic change take place as cells are transformed from normal to malignant. This review focuses on the use of different bioinformatics tools in cancer metabolomics studies. The article begins by describing different metabolomics technologies and data generation techniques. Overview of the data pre-processing techniques is provided and multivariate data analysis techniques are discussed and illustrated with case studies, including principal component analysis, clustering techniques, self-organizing maps, partial least squares, and discriminant function analysis. Also included is a discussion of available software packages.     

Clostridium difficile DNA polymerase IIIC: basis for activity of antibacterial compounds

Based on the finding that aerobic Gram-positive antibacterials that inhibit DNA polymerase IIIC (pol IIIC) were potent inhibitors of the growth of anaerobic Clostridium difficile (CD) strains, we chose to clone and express the gene for pol IIIC from this organism. The properties of the recombinant enzyme are similar to those of related pol IIICs from Gram-positive aerobes, e.g. B. subtilis. Inhibitors of the CD enzyme also inhibited B. subtilis pol IIIC, and were competitive with respect to the cognate substrate 2'-deoxyguanosine 5'-triphosphate (dGTP). Significantly, several of these inhibitors of the CD pol IIIC had potent activity against the growth of CD clinical isolates in culture.     

AGL24 acts in concert with SOC1 and FUL during Arabidopsis floral transition

Arabidopsis plants flower in response to long days (LDs). Exposure of leaves to inductive day lengths activates expression of FLOWERING LOCUS T (FT) protein which moves to the shoot apical meristem (SAM) to induce developmental reprogramming. SUPPRESSOR OF OVEREXPRESSION OF CONSTANS 1 (SOC1) and FRUITFULL (FUL) are induced by FT at the apex. We previously screened the SAM for mRNAs of genes required to promote the floral transition in response to photoperiod, and conducted detailed expression and functional analyses on several putative candidates. Here, we show that expression of AGAMOUS-LIKE 24 (AGL24) is detected at the SAM under SD conditions and increases upon exposure to LDs. Mutations in AGL24 further delay flowering of a soc1 ful double mutant, suggesting that flowering is controlled by AGL24 partly independently of SOC1 and FUL.     

Platelet activation by von Willebrand factor requires coordinated signaling through thromboxane A2 and Fc gamma IIA receptor

Interaction of von Willebrand Factor with glycoprotein Ib-IX-V induces platelet activation through a still poorly defined mechanism. Previous studies have suggested a possible role for the low affinity receptor for immunoglobulin, Fc gamma RIIA, in GPIb-IX-V signaling. Here we show that binding of vWF to platelets induces the tyrosine phosphorylation of Fc gamma RIIA by a Src kinase. Treatment of platelets with the anti-Fc gamma RIIA monoclonal antibody IV.3 specifically inhibits vWF-induced but not thrombin-induced pleckstrin phosphorylation and serotonin secretion. Moreover, vWF fails to induce pleckstrin phosphorylation in mouse platelets, lacking Fc gamma RIIA, and serotonin secretion is impaired. Pleckstrin phosphorylation and serotonin secretion in human platelets stimulated with vWF are blocked by the cyclooxygenase inhibitor acetylsalicylic acid. However, release of arachidonic acid and synthesis of TxA(2) induced by vWF are not affected by the anti-Fc gamma RIIA monoclonal antibody IV.3. Similarly, vWF-induced tyrosine phosphorylation of Fc gamma RIIA, as well as of Syk and PLC gamma 2, occurs normally in aspirinized platelets. Inhibition of the tyrosine kinase Syk by piceatannol does not affect vWF-induced tyrosine phosphorylation of Fc gamma RIIA but prevents phosphorylation of PLC gamma 2. Pleckstrin phosphorylation and platelet secretion induced by vWF, but not by thrombin, are also inhibited by piceatannol. Pleckstrin phosphorylation is also sensitive to the phosphatidylinositol 3-kinase inhibitor wortmannin. These results indicate that PLC gamma 2 plays a central role in platelet activation by vWF and that the stimulation of this enzyme requires coordinated signals through endogenous TxA(2) and Fc gamma RIIA.     

N-alkyl-4-[(8-azabicyclo[3.2.1]-oct-3-ylidene)phenylmethyl]benzamides, micro and delta opioid agonists: a micro address

The tertiary amide delta opioid agonist 2 is a potent antinociceptive agent. Compound 2 was metabolized in vitro and in vivo to secondary amide 3, a potent and selective micro opioid agonist. The SAR of a series of N-alkyl-4-[(8-azabicyclo[3.2.1]-oct-3-ylidene)phenylmethyl]benzamides was examined.     

Interaction of the low-molecular-weight GTP-binding protein rap2 with the platelet cytoskeleton is mediated by direct binding to the actin filaments

The interaction of the low-molecular-weight GTP-binding protein rap2 with the cytoskeleton from thrombin-aggregated platelets was investigated by inducing depolymerization of the actin filaments, followed by in vitro-promoted repolymerization. We found that the association of rap2 with the cytoskeleton was spontaneously restored after one cycle of actin depolymerization and repolymerization. Exogenous rap2, but not unrelated proteins, added to depolymerized actin and solubilized actin-binding proteins, was also specifically incorporated into the in vitro reconstituted cytoskeleton. The incorporation of exogenous rap2 was also observed when the cytoskeleton from resting or thrombin-activated platelets was subjected to actin depolymerization-repolymerization. Moreover, such interaction occurred equally well when exogenous rap2 was loaded with either GDP or GTPgammaS. We also found that polyhistidine-tagged rap2 immobilized on Ni(2+)-Sepharose and loaded with either GDP or GTPgammaS, could specifically bind to cytoskeletal actin. Moreover, when purified monomeric actin was induced to polymerize in vitro in the presence of rap2, the small G-protein specifically associated with the actin filaments. Finally, rap2 loaded with either GDP or GTPgammaS was able to bind to purified F-actin immobilized on a plastic surface. These results demonstrate that rap2 interacts with the platelet cytoskeleton by direct binding to the actin filaments and that this interaction is not regulated by the activation state of the protein.