Patient-specific simulation as a basis for clinical decision-making.

Patient-specific medical simulation holds the promise of determining tailored medical treatment based on the characteristics of an individual patient (for example, using a genotypic assay of a sequence of DNA). Decision-support systems based on patient-specific simulation can potentially revolutionize the way that clinicians plan courses of treatment for various conditions, ranging from viral infections to arterial abnormalities. Basing medical decisions on the results of simulations that use models derived from data specific to the patient in question means that the effectiveness of a range of potential treatments can be assessed before they are actually administered, preventing the patient from experiencing unnecessary or ineffective treatments. We illustrate the potential for patient-specific simulation by first discussing the scale of the evolving international grid infrastructure that is now available to underpin such applications. We then consider two case studies, one concerned with the treatment of patients with HIV/AIDS and the other addressing neuropathologies associated with the intracranial vasculature. Such patient-specific medical simulations require access to both appropriate patient data and the computational resources on which to perform potentially very large simulations. Computational infrastructure providers need to furnish access to a wide range of different types of resource, typically made available through heterogeneous computational grids, and to institute policies that facilitate the performance of patient-specific simulations on those resources. To support these kinds of simulations, where life and death decisions are being made, computational resource providers must give urgent priority to such jobs, for example by allowing them to pre-empt the queue on a machine and run straight away. We describe systems that enable such priority computing.

X box binding protein XBP-1s transactivates the Kaposi's sarcoma-associated herpesvirus (KSHV) ORF50 promoter, linking plasma cell differentiation to KSHV reactivation from latency.

Reactivation of lytic replication from viral latency is a defining property of all herpesviruses. Despite this, the authentic physiological cues for the latent-lytic switch are unclear. Such cues should ensure that viral lytic replication occurs under physiological conditions, predominantly in sites which facilitate transmission to permissive uninfected cells and new susceptible hosts. Kaposi's sarcoma-associated herpesvirus (KSHV) is associated with the B-cell neoplasm primary effusion lymphoma (PEL), in which the virus remains latent. We have previously shown that PEL cells have the gene expression profile and immunophenotype of cycling preplasma cells (plasmablasts). Here, we show that the highly active spliced isoform of plasma cell transcription factor X box binding protein 1 (XBP-1s) is a lytic switch for KSHV. XBP-1s is normally absent in PEL, but the induction of endoplasmic reticulum stress leads to XBP-1s generation, plasma cell-like differentiation, and lytic reactivation of KSHV. XBP-1s binds to and activates the KSHV immediate-early gene ORF50 and synergizes with the ORF50 gene product RTA to induce a full lytic cycle. These data suggest that KSHV remains latent until B-cell terminal differentiation into plasma cells, the transcriptional environment of which provides the physiological "lytic switch" through XBP-1s. This links B-cell terminal differentiation to KSHV lytic reactivation.

Genotypic variation in the pol gene of HIV type 1 in an antiretroviral treatment-naive population in rural southwestern Uganda.

The majority of studies of HIV-1 drug resistance have involved subtype B viruses. Here we have characterized subtype distribution and determined the levels of polymorphism at protease (PR) and reverse transcriptase (RT) drug resistance positions, in antiretroviral treatment-naive HIV-positive Ugandan patients. We have also investigated codon usage variability at these positions and assessed intersubtype recombination within the pol gene. The study population consisted of 187 patients, from a cohort established by the UK Medical Research Council Programme on AIDS in Uganda in 1990. Results indicate that 28.3% of patients were infected with subtype A (n = 53), 64.2% subtype D (n = 120), 6.4% A/D recombinant (n = 12), and 1.1% subtype C (n = 2). Variation in amino acid usage at drug resistance-associated positions was minimal between the two main subtypes (A and D) in RT, but there was appreciable variation in PR. Codon usage, however, was considerably more variable between subtypes A and D in both PR and RT. Thus, while no natural high-level resistance to antiretroviral therapy was detected in this cohort, subtypes A and D may possess different genetic barriers to be overcome in order to achieve resistance. With the increasing introduction of antiretroviral therapy into Africa, such information will be vital in our understanding and evaluation of the development of drug resistance as it occurs, and how to interpret resistance data the type of which has rarely previously been seen. This analysis also significantly increases the number of Ugandan PR and RT sequences characterized to date.

Assessment of automated genotyping protocols as tools for surveillance of HIV-1 genetic diversity.

BACKGROUND: The routine use of drug resistance testing provides an abundant source of HIV-1 sequence data. However, it is not clear how reliable standard genotyping of these sequences is for describing HIV-1 genetic variation and for detecting novel genetic variants and epidemiological trends. OBJECTIVES: To compare assignment of HIV-1 resistance test sequences to reference strains across commonly used genotyping protocols. METHODS: Subtype assignments were compared across three standard genotyping protocols for 10 537 resistance test sequences, representing approximately one-fifth of all reported infections in the United Kingdom. Sequences that were inconsistently genotyped across methods, or that were unassigned by at least one method, were examined for evidence of recombination using sliding-window-based approaches. RESULTS: Although agreement across methods was high for subtypes B, C and H, it was generally much lower (< 50%) for other subtypes. Disagreement between methods typically involved closely related, but epidemiologically distinct, groups or involved a significant proportion ( approximately 12%) of divergent sequences in which analysis revealed widespread evidence of recombination and a remarkable diversity of unusual recombinant forms. CONCLUSIONS: With frequent long-distance transfer of viral strains and widespread recombination between them, genetic and epidemiological relationships within HIV-1 are becoming increasingly complex. Current methods of subtype assignment vary in their ability to identify novel genetic variants and to distinguish epidemiologically distinct strains. Capturing meaningful epidemiological information from resistance test data will require a critical understanding of the methodologies used in order to appreciate the possible sources of error and misclassification.

Development of a novel human immunodeficiency virus type 1 subtyping tool, Subtype Analyzer (STAR): analysis of subtype distribution in London.

We have developed a high throughput computational tool for assigning subtype to HIV-1, based solely on protease and reverse transcriptase (PR-RT) amino acid sequence, generated routinely for clinical assessment of genotypic drug resistance. Subtype-specific profiles were created by generation of position-specific scoring matrices (PSSMs) from multiple amino acids alignments of HIV-1 sequence data from GenBank, phylogenetically divided into subtypes A, AG, B, C, D, F/K, G, H, and J and the separate groups N and O. Query sequences of unknown subtype are aligned with these profiles and a score is derived by comparing each amino acid position in the unknown sequence to the normalized frequency distribution of amino acids at the corresponding positions in the subtype alignments. The highest score is used to assign subtype to the query sequence. Leave one out cross-validation analysis showed the Subtype Analyzer (STAR) was 99% accurate in subtype assignation. STAR can be updated with additional subtype-specific sequence data from sequence databases. STAR was used to classify HIV-1 PR-RT sequences from 843 HIV-1 clinical isolates submitted for drug resistance profiling in London. Within this dataset 26.9% of sequences were classified by STAR as non-B subtypes.

Inclusion of full length human immunodeficiency virus type 1 (HIV-1) gag sequences in viral recombinants applied to drug susceptibility phenotyping.

Drug susceptibility phenotyping of recombinant clinical human immunodeficiency virus type 1 (HIV-1) isolates has been used widely to quantitatively assess viral resistance to antiretroviral agents. A novel method is described for HIV-1 drug susceptibility phenotyping. Recombinant virus that contains the entire HIV-1 Gag, protease (PR) and reverse transcriptase (RT) coding regions is generated from plasma of HIV-1 infected subjects, thus allowing the in vitro investigation of effects caused by all protein-coding sequence elements upstream from the drug targets on: (i) drug susceptibility; and (ii) viral replicative capacity. Mutations known to cause retarded viral growth kinetics (RT M184V and PR I50V) were introduced and analyzed in parallel using both the new Five Prime HIV assay (FPH) and a standard recombinant virus assay (RVA). The M184V and I50V mutants produced up to 4.8- and 5.9-fold higher p24 antigen levels, respectively, with the FPH when compared to the cultures containing RVA-derived viruses. The reduced number of homologous recombination events necessary to generate replication-competent provirus with the FPH is the most likely explanation for these findings. Long range RT-PCR products were generated from plasma of HIV-1 infected subjects and HIV-1 LTR sequences were added using one-step PCR-mediated recombination. FPH-recombinants generated from two patients with previous HIV PR and RT inhibitor therapy showed lower drug susceptibilities than mutants established in parallel by RVA, and relative in vitro replication of the FPH recombinant derived from one of these subjects was enhanced compared to the corresponding RVA mutant. Although there were changes from the HIV-1 subtype B consensus sequence in amino acids flanking the Gag p17/p24, p24/p2 or p2/p7 PR cleavage sites, none were within the 10 amino acids immediately flanking the sites. These data suggest that determinants of drug susceptibility may be encoded in Gag upstream of the p7/p1 and p1/p6 regions, and that some phenotyping assays may therefore be underdetermining the reduction of drug susceptibility in some viral isolates.