Many biological processes are RNA-mediated, but higher-order structures for most RNAs are unknown, making it difficult to understand how RNA structure governs function. Here we describe SHAPE mutational profiling (SHAPE-MaP) that makes possible de novo and large-scale identification of RNA functional motifs. Sites of 2’-hydroxyl acylation by SHAPE are encoded as non-complementary nucleotides during cDNA synthesis, as measured by massively parallel sequencing. SHAPE-MaP-guided modeling identified greater than 90% of accepted base pairs in complex RNAs of known structure and was used to define a second-generation model for the HIV-1 RNA genome. The HIV-1 model contains all known structured motifs and previously unknown elements, including experimentally validated pseudoknots. SHAPE-MaP yields accurate and high-resolution secondary structure models, enables analysis of low abundance RNAs, disentangles sequence polymorphisms in single experiments, and will ultimately democratize RNA structure analysis.

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This model is predictive of recent PrEP trial results in which 2-3 doses/week was 75%-90% effective in men but ineffective in women. These data provide a novel approach for future PrEP investigations that can optimize clinical trial dosing strategies.

Background Over 150 000 Malawians have started antiretroviral therapy (ART), in which first-line therapy is stavudine/lamivudine/nevirapine. We evaluated drug resistance patterns among patients failing first-line ART on the basis of clinical or immunological criteria in Lilongwe and Blantyre, Malawi. Methods Patients meeting the definition of ART failure (new or progressive stage 4 condition, CD4 cell count decline more than 30%, CD4 cell count less than that before treatment) from January 2006 to July 2007 were evaluated. Among those with HIV RNA of more than 1000 copies/ml, genotyping was performed. For complex genotype patterns, phenotyping was performed. Results Ninety-six confirmed ART failure patients were identified. Median (interquartile range) CD4 cell count, log10 HIV-1 RNA, and duration on ART were 68 cells/μl (23–174), 4.72 copies/ml (4.26–5.16), and 36.5 months (26.6–49.8), respectively. Ninety-three percent of samples had nonnucleoside reverse transcriptase inhibitor mutations, and 81% had the M184V mutation. The most frequent pattern included M184V and nonnucleoside reverse transcriptase inhibitor mutations along with at least one thymidine analog mutation (56%). Twenty-three percent of patients acquired the K70E or K65R mutations associated with tenofovir resistance; 17% of the patients had pan-nucleoside resistance that corresponded to K65R or K70E and additional resistance mutations, most commonly the 151 complex. Emergence of the K65R and K70E mutations was associated with CD4 cell count of less than 100 cells/μl (odds ratio 6.1) and inversely with the use of zidovudine (odds ratio 0.18). Phenotypic susceptibility data indicated that the nucleoside reverse transcriptase inhibitor backbone with the highest activity for subsequent therapy was zidovudine/lamivudine/tenofovir, followed by lamivudine/tenofovir, and then abacavir/didanosine. Conclusion When clinical and CD4 cell count criteria are used to monitor first-line ART failure, extensive nucleoside reverse transcriptase inhibitor and nonnucleoside reverse transcriptase inhibitor resistance emerges, with most patients having resistance profiles that markedly compromise the activity of second-line ART.