Human TOP1 residues implicated in species specificity of HIV-1 infection are required for interaction with BTBD2, and RNAi of BTBD2 in old world monkey and human cells increases permissiveness to HIV-1 infection

Host determinants of HIV-1 viral tropism include factors from producer cells that affect the efficiency of productive infection and factors in target cells that block infection after viral entry. TRIM5 restricts HIV-1 infection at an early post-entry step through a mechanism associated with rapid disassembly of the retroviral capsid. Topoisomerase I (TOP1) appears to play a role in HIV-1 viral tropism by incorporating into or otherwise modulating virions affecting the efficiency of a post-entry step, as the expression of human TOP1 in African Green Monkey (AGM) virion-producing cells increased the infectivity of progeny virions by five-fold. This infectivity enhancement required human TOP1 residues 236 and 237 as their replacement with the AGM counterpart residues abolished the infectivity enhancement. Our previous studies showed that TOP1 interacts with BTBD1 and BTBD2, two proteins which co-localize with the TRIM5 splice variant TRIM5 in cytoplasmic bodies. Because BTBD1 and BTBD2 interact with one HIV-1 viral tropism factor, TOP1, and co-localize with a splice variant of another, we investigated the potential involvement of BTBD1 and BTBD2 in HIV-1 restriction.

Whole genome RNAi screens reveal a critical role of REV3 in coping with replication stress

REV3, the catalytic subunit of translesion polymerase zeta (polζ), is commonly associated with DNA damage bypass and repair. Despite sharing accessory subunits with replicative polymerase δ, very little is known about the role of polζ in DNA replication. We previously demonstrated that inhibition of REV3 expression induces persistent DNA damage and growth arrest in cancer cells. To reveal determinants of this sensitivity and obtain insights into the cellular function of REV3, we performed whole human genome RNAi library screens aimed at identification of synthetic lethal interactions with REV3 in A549 lung cancer cells. The top confirmed hit was RRM1, the large subunit of ribonucleotide reductase (RNR), a critical enzyme of de novo nucleotide synthesis. Treatment with the RNR-inhibitor hydroxyurea (HU) synergistically increased the fraction of REV3-deficient cells containing single stranded DNA (ssDNA) as indicated by an increase in replication protein A (RPA). However, this increase was not accompanied by accumulation of the DNA damage marker γH2AX suggesting a role of REV3 in counteracting HU-induced replication stress (RS). Consistent with a role of REV3 in DNA replication, increased RPA staining was confined to HU-treated S-phase cells. Additionally, we found genes related to RS to be significantly enriched among the top hits of the synthetic sickness/lethality (SSL) screen further corroborating the importance of REV3 for DNA replication under conditions of RS.

Simulating Energy Transfer and Upconversion in β-NaYF 4 : Yb 3+ , Tm 3+

The design of upconversion phosphors with higher quantum yield requires a deeper understanding of the detailed energy transfer and upconversion processes between active ions inside the material. Rate equations can model those processes by describing the populations of the energy levels of the ions as a function of time. However, this model presents some drawbacks: energy migration is assumed to be infinitely fast, it does not determine the detailed interaction mechanism (multipolar or exchange), and it only provides the macroscopic averaged parameters of interaction. Hence, a rate equation model with the same parameters cannot correctly predict the time evolution of upconverted emission and power dependence under a wide range of concentrations of active ions. We present a model that combines information about the host material lattice, the concentration of active ions, and a microscopic rate equation system. The extent of energy migration is correctly taken into account because the energy transfer processes are described on the level of the individual ions. This model predicts the decay curves, concentration, and excitation power dependences of the emission. This detailed information can be used to predict the optimal concentration that results in the maximum upconverted emission.