Biomedical subjects

Angélique B van 't Wout

Publications and source records attributed to Angélique B van 't Wout.

7 recordsLinked to original sources

PubMed2006

T cell line passage can select for pre-existing neutralization-sensitive variants from the quasispecies of primary human immunodeficiency virus type-1 isolates.

Primary human immunodeficiency type 1 viruses (HIV-1) resist antibody neutralization but become sensitive after passage through T cell lines. We and others previously reported an increased neutralization sensitivity of HIV-1 after prolonged culture on primary peripheral blood mononuclear cells (PBMC). Hence we hypothesized that adaptation to growth in T cell lines is in fact selection of a pre-existing neutralization-sensitive HIV-1 variant from the quasispecies in the PBMC culture. Indeed, increased neutralization sensitivity was associated with largely identical synonymous and non-synonymous mutations between progeny of parallel H9 passages from the same split inoculum from 2 of 3 viruses. H9 T cell line adaptation of molecular cloned HIV-1 was less successful and associated with only a few de novo mutations that varied between parallel H9-adapted progeny from the same split inoculum. We conclude that T cell line adaptation of HIV-1 can indeed select for a pre-existing variant but that this most likely depends on the viral diversity in the inoculum.

Adaptation, Physiological↗

PubMed2006

A reliable phenotype predictor for human immunodeficiency virus type 1 subtype C based on envelope V3 sequences.

In human immunodeficiency virus type 1 (HIV-1) subtype B infections, the emergence of viruses able to use CXCR4 as a coreceptor is well documented and associated with accelerated CD4 decline and disease progression. However, in HIV-1 subtype C infections, responsible for more than 50% of global infections, CXCR4 usage is less common, even in individuals with advanced disease. A reliable phenotype prediction method based on genetic sequence analysis could provide a rapid and less expensive approach to identify possible CXCR4 variants and thus increase our understanding of subtype C coreceptor usage. For subtype B V3 loop sequences, genotypic predictors have been developed based on position-specific scoring matrices (PSSM). In this study, we apply this methodology to a training set of 279 subtype C sequences of known phenotypes (228 non-syncytium-inducing [NSI] CCR5(+) and 51 SI CXCR4(+) sequences) to derive a C-PSSM predictor. Specificity and sensitivity distributions were estimated by combining data set bootstrapping with leave-one-out cross-validation, with random sampling of single sequences from individuals on each bootstrap iteration. The C-PSSM had an estimated specificity of 94% (confidence interval [CI], 92% to 96%) and a sensitivity of 75% (CI, 68% to 82%), which is significantly more sensitive than predictions based on other methods, including a commonly used method based on the presence of positively charged residues (sensitivity, 47.8%). A specificity of 83% and a sensitivity of 83% were achieved with a validation set of 24 SI and 47 NSI unique subtype C sequences. The C-PSSM performs as well on subtype C V3 loops as existing subtype B-specific methods do on subtype B V3 loops. We present bioinformatic evidence that particular sites may influence coreceptor usage differently, depending on the subtype.

HIV Envelope Protein gp120↗

PubMed2005

Nef induces multiple genes involved in cholesterol synthesis and uptake in human immunodeficiency virus type 1-infected T cells.

Several recent reports indicate that cholesterol might play an important role in human immunodeficiency virus type 1 (HIV-1) replication. We investigated the effects of HIV-1 infection on cholesterol biosynthesis and uptake using microarrays. HIV-1 increased gene expression of cholesterol genes in both transformed T-cell lines and primary CD4(+) T cells. Consistent with our microarray data, (14)C-labeled mevalonate and acetate incorporation was increased in HIV-1-infected cells. Our data also demonstrate that changes in cholesterol biosynthesis and uptake are only observed in the presence of functional Nef, suggesting that increased cholesterol synthesis may contribute to Nef-mediated enhancement of virion infectivity and viral replication.

Aspartic Acid Endopeptidases↗

PubMed2005

Gene expression profiling of HIV-1 infection using cDNA microarrays.

To illustrate the methods employed in gene expression profiling using cDNA microarrays, infection of CD4+ T cell lines with HIV-1LAI is used to identify expression changes relevant to in vitro HIV-1 infection. Cell lines are infected at a high multiplicity of infection to ensure a population of near-synchronously infected cells to be compared to uninfected cells. Infection status is verified using flow cytometry to determine the intracellular expression of the viral gag p24 protein before samples are harvested for total RNA extraction. Total RNA is extracted and amplified using commercially available kits, and RNA quality is verified using Bioanalyzer technology. To obtain fluorescently labeled cDNA probes, the amplified RNA is reverse-transcribed to yield cDNA, using random nonamers in the presence of dye-labeled dCTP. After first-strand cDNA synthesis, RNA is degraded and the probes are purified. For each infection condition (LAI and mock), two slides are hybridized with identical probes generated from the same RNAs, but with fluorescent labels reversed on one of the slides to control for dye-specific effects. Troubleshooting strategies and issues to consider prior to starting the experiment are discussed in detail in the notes section.

CD4-Positive T-Lymphocytes↗

PubMed2003

Cellular gene expression upon human immunodeficiency virus type 1 infection of CD4(+)-T-cell lines.

The expression levels of approximately 4,600 cellular RNA transcripts were assessed in CD4(+)-T-cell lines at different times after infection with human immunodeficiency virus type 1 strain BRU (HIV-1(BRU)) using DNA microarrays. We found that several classes of genes were inhibited by HIV-1(BRU) infection, consistent with the G(2) arrest of HIV-1-infected cells induced by Vpr. These included genes involved in cell division and transcription, a family of DEAD-box proteins (RNA helicases), and all genes involved in translation and splicing. However, the overall level of cell activation and signaling was increased in infected cells, consistent with strong virus production. These included a subgroup of transcription factors, including EGR1 and JUN, suggesting they play a specific role in the HIV-1 life cycle. Some regulatory changes were cell line specific; however, the majority, including enzymes involved in cholesterol biosynthesis, of changes were regulated in most infected cell lines. Compendium analysis comparing gene expression profiles of our HIV-1 infection experiments to those of cells exposed to heat shock, interferon, or influenza A virus indicated that HIV-1 infection largely induced specific changes rather than simply activating stress response or cytokine response pathways. Thus, microarray analysis confirmed several known HIV-1 host cell interactions and permitted identification of specific cellular pathways not previously implicated in HIV-1 infection. Continuing analyses are expected to suggest strategies for impacting HIV-1 replication in vivo by targeting these pathways.

Base Sequence↗

PubMed2003

Improved coreceptor usage prediction and genotypic monitoring of R5-to-X4 transition by motif analysis of human immunodeficiency virus type 1 env V3 loop sequences.

Early in infection, human immunodeficiency virus type 1 (HIV-1) generally uses the CCR5 chemokine receptor (along with CD4) for cellular entry. In many HIV-1-infected individuals, viral genotypic changes arise that allow the virus to use CXCR4 (either in addition to CCR5 or alone) as an entry coreceptor. This switch has been associated with an acceleration of both CD3(+) T-cell decline and progression to AIDS. While it is well known that the V3 loop of gp120 largely determines coreceptor usage and that positively charged residues in V3 play an important role, the process of genetic change in V3 leading to altered coreceptor usage is not well understood. Further, the methods for biological phenotyping of virus for research or clinical purposes are laborious, depend on sample availability, and present biosafety concerns, so reliable methods for sequence-based "virtual phenotyping" are desirable. We introduce a simple bioinformatic method of scoring V3 amino acid sequences that reliably predicts CXCR4 usage (sensitivity, 84%; specificity, 96%). This score (as determined on the basis of position-specific scoring matrices [PSSM]) can be interpreted as revealing a propensity to use CXCR4 as follows: known R5 viruses had low scores, R5X4 viruses had intermediate scores, and X4 viruses had high scores. Application of the PSSM scoring method to reconstructed virus phylogenies of 11 longitudinally sampled individuals revealed that the development of X4 viruses was generally gradual and involved the accumulation of multiple amino acid changes in V3. We found that X4 viruses were lost in two ways: by the dying off of an established X4 lineage or by mutation back to low-scoring V3 loops.

Computational Biology↗

PubMedDate not supplied

Predicting HIV-1 coreceptor usage with sequence analysis.

Bioinformatics approaches are increasingly being used to identify and understand the genetic variation underlying changes in HIV-1 biological phenotype. The variable regions of the viral envelope are the major determinant of virus coreceptor usage and cell tropism. Specifically, amino acids 11 and 25 in the 3rd variable (V3) loop have been found to strongly influence viral syncytium inducing capacity and coreceptor usage. Many additional V3 loop changes, however, as well as changes elsewhere in Env, are thought to contribute to phenotype. In this review we describe several recently developed methods to analyze this variability and their use to predict biological phenotype based on sequence information. These approaches have identified changes in the V3 loop, in addition to the known changes at positions 11 and 25, that affect phenotype and significantly enhance our ability to predict phenotype from genotype. Besides improving phenotype prediction, methods that score V3 sequences on a continuous scale can also assist in the interpretation of evolutionary information about shifts in phenotype, and the relationship between that evolution and pathogenesis. Several examples and potential practical applications of this scoring are discussed. We conclude that advances in computational approaches have enhanced both our ability to predict and to understand HIV-1 biological phenotype evolution. Further development of these methods, by extending analysis to regions outside the V3 loop and to clades beyond subtype B, will extend our understanding of HIV-1 pathogenesis and inform treatment strategies.

Computational Biology↗