Extended spectrum of HIV-1 reverse transcriptase mutations in patients receiving multiple nucleoside analog inhibitors.

OBJECTIVE: To characterize reverse transcriptase (RT) mutations by their association with extent of nucleoside RT inhibitor (NRTI) therapy. To identify mutational clusters in RT sequences from persons receiving multiple NRTI. DESIGN: A total of 1210 RT sequences from persons with known antiretroviral therapy were analyzed: 641 new sequences were performed at Stanford University Hospital; 569 were previously published. METHODS: Chi-square tests and logistic regression were done to identify associations between mutations and NRTI therapy. Correlation studies were done to identify mutational clusters. The Benjamini-Hochberg procedure was used to correct for multiple comparisons. RESULTS: Mutations at 26 positions were significantly associated with NRTI including 17 known resistance mutations (positions 41, 44, 62, 65, 67, 69, 70, 74, 75, 77, 116, 118, 151, 184, 210, 215, 219) and nine previously unreported mutations (positions 20, 39, 43, 203, 208, 218, 221, 223, 228). The nine new mutations correlated linearly with number of NRTI; 777 out of 817 (95%) instances occurred with known drug resistance mutations. Positions 203, 208, 218, 221, 223, and 228 were conserved in untreated persons; positions 20, 39, and 43 were polymorphic. Most NRTI-associated mutations clustered into three groups: (i) 62, 65, 75, 77, 115, 116, 151; (ii) 41, 43, 44, 118, 208, 210, 215, 223; (iii) 67, 69, 70, 218, 219, 228. CONCLUSIONS: Mutations at nine previously unreported positions are associated with NRTI therapy. These mutations are probably accessory because they occur almost exclusively with known drug resistance mutations. Most NRTI mutations group into one of three clusters, although several (e.g., M184V) occur in multiple mutational contexts.

Protease and reverse transcriptase mutation patterns in HIV type 1 isolates from heavily treated persons: comparison of isolates from Northern California with isolates from other regions.

We compared HIV-1 subtype B reverse transcriptase (RT) and protease mutation patterns in isolates from heavily treated persons in Northern California with those from persons described in the published literature predominantly from other parts of the United States and Europe. There were few differences in the prevalence of single, double, and triple mutations between the two sets of sequences. More complex patterns of mutations could be characterized by clustering the sequences into eight groups of RT sequences and nine groups of protease sequences according to the presence of known drug-resistance mutations. This clustering accounted for 63% of the variation at RT inhibitor-resistance positions and 68% of the variation at protease inhibitor-resistance positions. The majority of clusters contained Northern California and literature sequences in similar proportions.

Automatic clustering of flow cytometry data with density-based merging.

The ability of flow cytometry to allow fast single cell interrogation of a large number of cells has made this technology ubiquitous and indispensable in the clinical and laboratory setting. A current limit to the potential of this technology is the lack of automated tools for analyzing the resulting data. We describe methodology and software to automatically identify cell populations in flow cytometry data. Our approach advances the paradigm of manually gating sequential two-dimensional projections of the data to a procedure that automatically produces gates based on statistical theory. Our approach is nonparametric and can reproduce nonconvex subpopulations that are known to occur in flow cytometry samples, but which cannot be produced with current parametric model-based approaches. We illustrate the methodology with a sample of mouse spleen and peritoneal cavity cells.

Aerosolized gamma interferon (IFN-gamma) induces expression of the genes encoding the IFN-gamma-inducible 10-kilodalton protein but not inducible nitric oxide synthase in the lung during tuberculosis.

Gamma interferon (IFN-gamma) is critical in the immune response against Mycobacterium tuberculosis. In an ongoing trial of aerosol IFN-gamma in conjunction with standard drug therapy, we have observed activation of IFN signaling in bronchoalveolar lavage (BAL) cells from tuberculosis (TB) patients. We hypothesized that aerosol IFN-gamma treatment of pulmonary TB would increase expression of genes important for the control of TB. We investigated the expression of downstream genes by measuring inducible nitric oxide synthase (iNOS) and the chemokine IFN-inducible 10-kDa protein (IP-10) by real-time quantitative reverse transcription-PCR. In vitro, M. tuberculosis induced IP-10, and IFN-gamma stimulated this further, with no effect on iNOS expression. We studied 21 patients with pulmonary TB and 7 healthy subjects. Similar to the in vitro model, IP-10 mRNA was increased in BAL cells from TB patients and was augmented after treatment with aerosolized IFN-gamma. TB was also associated with elevated iNOS mRNA, but aerosolized IFN-gamma did not further enhance expression. Genomic analysis identified 1,300 of 4,058 genes expressed in BAL cells from six TB patients before and after 1 month of therapy, including aerosolized IFN-gamma. However, only 15 genes were differentially regulated by IFN-gamma. We conclude that iNOS and IP-10 mRNA expression is increased in TB but that aerosol IFN-gamma treatment increases expression of few genes in the human lung.