Geographic and temporal trends in the molecular epidemiology and genetic mechanisms of transmitted HIV-1 drug resistance:an individual-patient- and sequence-level meta-analysis

Regional and subtype-specific mutational patterns of HIV-1 transmitted drug resistance (TDR) are essential for informing first-line antiretroviral (ARV) therapy guidelines and designing diagnostic assays for use in regions where standard genotypic resistance testing is not affordable. We sought to understand the molecular epidemiology of TDR and to identify the HIV-1 drug-resistance mutations responsible for TDR in different regions and virus subtypes.status: publishe

Glutathione-dependent redox balance characterizes the distinct metabolic properties of follicular and marginal zone B cells

The metabolic principles underlying the differences between follicular and marginal zone B cells (FoB and MZB, respectively) are not well understood. Here we show, by studying mice with B cell-specific ablation of the catalytic subunit of glutamate cysteine ligase (Gclc), that glutathione synthesis affects homeostasis and differentiation of MZB to a larger extent than FoB, while glutathione-dependent redox control contributes to the metabolic dependencies of FoB. Specifically, Gclc ablation in FoB induces metabolic features of wild-type MZB such as increased ATP levels, glucose metabolism, mTOR activation, and protein synthesis. Furthermore, Gclc-deficient FoB have a block in the mitochondrial electron transport chain (ETC) due to diminished complex I and II activity and thereby accumulate the tricarboxylic acid cycle metabolite succinate. Finally, Gclc deficiency hampers FoB activation and antibody responses in vitro and in vivo, and induces susceptibility to viral infections. Our results thus suggest that Gclc is required to ensure the development of MZB, the mitochondrial ETC integrity in FoB, and the efficacy of antiviral humoral immunity. Follicular and marginal zone B (FoB and MZB, respectively) cells have divergent metabolic characteristics. Here the authors show that deficiency of glutamate cysteine ligase (Gclc), the enzyme for glutathione synthesis, differentially impacts FoB and MZB homeostasis, while specifically impeding FoB activation and downstream antiviral immunity

Discordances between Interpretation Algorithms for Genotypic Resistance to Protease and Reverse Transcriptase Inhibitors of Human Immunodeficiency Virus Are Subtype Dependent

The major limitation of drug resistance genotyping for human immunodeficiency virus remains the interpretation of the results. We evaluated the concordance in predicting therapy response between four different interpretation algorithms (Rega 6.3, HIVDB-08/04, ANRS [07/04], and VGI 8.0). Sequences were gathered through a worldwide effort to establish a database of non-B subtype sequences, and demographic and clinical information about the patients was gathered. The most concordant results were found for nonnucleoside reverse transcriptase (RT) inhibitors (93%), followed by protease inhibitors (84%) and nucleoside RT inhibitor (NRTIs) (76%). For therapy-naive patients, for nelfinavir, especially for subtypes C and G, the discordances were driven mainly by the protease (PRO) mutational pattern 82I/V + 63P + 36I/V for subtype C and 82I + 63P + 36I + 20I for subtype G. Subtype F displayed more discordances for ritonavir in untreated patients due to the combined presence of PRO 20R and 10I/V. In therapy-experienced patients, subtype G displayed a lot of discordances for saquinavir and indinavir due to mutational patterns involving PRO 90 M and 82I. Subtype F had more discordance for nelfinavir attributable to the presence of PRO 88S and 82A + 54V. For the NRTIs lamivudine and emtricitabine, CRF01_AE had more discordances than subtype B due to the presence of RT mutational patterns 65R + 115 M and 118I + 215Y, respectively. Overall, the different algorithms agreed well on the level of resistance scored, but some of the discordances could be attributed to specific (subtype-dependent) combinations of mutations. It is not yet known whether therapy response is subtype dependent, but the advice given to clinicians based on a genotypic interpretation algorithm differs according to the subtype