E1B-55K-Mediated Regulation of RNF4 SUMO-Targeted Ubiquitin Ligase Promotes Human Adenovirus Gene Expression

Human adenovirus (HAdV) E1B-55K is a multifunctional regulator of productive viral replication and oncogenic transformation in nonpermissive mammalian cells. These functions depend on E1B-55K's posttranslational modification with the SUMO protein and its binding to HAdV E4orf6. Both early viral proteins recruit specific host factors to form an E3 ubiquitin ligase complex that targets antiviral host substrates for proteasomal degradation. Recently, we reported that the PML-NB-associated factor Daxx represses efficient HAdV productive infection and is proteasomally degraded via a SUMO-E1B-55K-dependent, E4orf6-independent pathway, the details of which remained to be established. RNF4, a cellular SUMO-targeted ubiquitin ligase (STUbL), induces ubiquitinylation of specific SUMOylated proteins and plays an essential role during DNA repair. Here, we show that E1B-55K recruits RNF4 to the insoluble nuclear matrix fraction of the infected cell to support RNF4/Daxx association, promoting Daxx PTM and thus inhibiting this antiviral factor. Removing RNF4 from infected cells using RNA interference resulted in blocking the proper establishment of viral replication centers and significantly diminished viral gene expression. These results provide a model for how HAdV antagonize the antiviral host responses by exploiting the functional capacity of cellular STUbLs. Thus, RNF4 and its STUbL function represent a positive factor during lytic infection and a novel candidate for future therapeutic antiviral intervention strategies.IMPORTANCE Daxx is a PML-NB-associated transcription factor that was recently shown to repress efficient HAdV productive infection. To counteract this antiviral measurement during infection, Daxx is degraded via a novel pathway including viral E1B-55K and host proteasomes. This virus-mediated degradation is independent of the classical HAdV E3 ubiquitin ligase complex, which is essential during viral infection to target other host antiviral substrates. To maintain a productive viral life cycle, HAdV E1B-55K early viral protein inhibits the chromatin-remodeling factor Daxx in a SUMO-dependent manner. In addition, viral E1B-55K protein recruits the STUbL RNF4 and sequesters it into the insoluble fraction of the infected cell. E1B-55K promotes complex formation between RNF4- and E1B-55K-targeted Daxx protein, supporting Daxx posttranslational modification prior to functional inhibition. Hence, RNF4 represents a novel host factor that is beneficial for HAdV gene expression by supporting Daxx counteraction. In this regard, RNF4 and other STUbL proteins might represent novel targets for therapeutic intervention

Modulation of human endogenous retrovirus (HERV) transcription during persistent and de novo HIV-1 infection

Background: The human genome contains multiple LTR elements including human endogenous retroviruses (HERVs) that together account for approximately 8–9% of the genomic DNA. At least 40 different HERV groups have been assigned to three major HERV classes on the basis of their homologies to exogenous retroviruses. Although most HERVs are silenced by a variety of genetic and epigenetic mechanisms, they may be reactivated by environmental stimuli such as exogenous viruses and thus may contribute to pathogenic conditions. The objective of this study was to perform an in-depth analysis of the influence of HIV-1 infection on HERV activity in different cell types. Results: A retrovirus-specific microarray that covers major HERV groups from all three classes was used to analyze HERV transcription patterns in three persistently HIV-1 infected cell lines of different cellular origins and in their uninfected counterparts. All three persistently infected cell lines showed increased transcription of multiple class I and II HERV groups. Up-regulated transcription of five HERV taxa (HERV-E, HERV-T, HERV-K (HML-10) and two ERV9 subgroups) was confirmed by quantitative reverse transcriptase PCR analysis and could be reversed by knock-down of HIV-1 expression with HIV-1-specific siRNAs. Cells infected de novo by HIV-1 showed stronger transcriptional up-regulation of the HERV-K (HML-2) group than persistently infected cells of the same origin. Analysis of transcripts from individual members of this group revealed up-regulation of predominantly two proviral loci (ERVK-7 and ERVK-15) on chromosomes 1q22 and 7q34 in persistently infected KE37.1 cells, as well as in de novo HIV-1 infected LC5 cells, while only one single HML-2 locus (ERV-K6) on chromosome 7p22.1 was activated in persistently infected LC5 cells. Conclusions: Our results demonstrate that HIV-1 can alter HERV transcription patterns of infected cells and indicate a correlation between activation of HERV elements and the level of HIV-1 production. Moreover, our results suggest that the effects of HIV-1 on HERV activity may be far more extensive and complex than anticipated from initial studies with clinical material

Acriflavine, a clinically approved drug, inhibits SARS-CoV-2 and other betacoronaviruses

The COVID-19 pandemic caused by SARS-CoV-2 has been socially and economically devastating. Despite an unprecedented research effort and available vaccines, effective therapeutics are still missing to limit severe disease and mortality. Using high-throughput screening, we identify acriflavine (ACF) as a potent papain-like protease (PLpro) inhibitor. NMR titrations and a co-crystal structure confirm that acriflavine blocks the PLpro catalytic pocket in an unexpected binding mode. We show that the drug inhibits viral replication at nanomolar concentration in cellular models, in vivo in mice and ex vivo in human airway epithelia, with broad range activity against SARS-CoV-2 and other betacoronaviruses. Considering that acriflavine is an inexpensive drug approved in some countries, it may be immediately tested in clinical trials and play an important role during the current pandemic and future outbreaks. © 2021 The Author

Heterogenous nuclear ribonucleoprotein Q increases protein expression from HIV-1 Rev-dependent transcripts

BACKGROUND: Heterogenous nuclear ribonucleoproteins (hnRNPs) control many processes of the gene expression machinery including mRNA transcription, splicing, export, stability and translation. Recent data show interaction of the HIV-1 Rev regulatory protein with a subset of hnRNP proteins, that includes hnRNP Q, suggesting that hnRNPs can contribute to regulation of HIV-1 gene expression by Rev. FINDINGS: In this work we address the effect of hnRNP Q on Rev-dependent gene expression. We show that hnRNP Q overexpression increased levels of proteins produced from a Rev-dependent reporter gene in the presence of Rev. Increased protein levels did not correlate with changes in either the levels or the nucleocytoplasmic distribution of Rev-dependent reporter mRNAs. Similar observations were made in persistently HIV-1 infected HeLa cells. In these cells, hnRNP Q overexpression increased levels of the HIV-1 Gag-p24 protein, while levels of viral Rev-dependent mRNAs were not affected. CONCLUSION: Our data indicate that hnRNP Q can stimulate the protein production of Rev-dependent mRNAs without changing mRNA levels and mRNA export, respectively. This suggests that hnRNP Q can boost HIV gene expression at the level of protein production

Machine learning classifies ferroptosis and apoptosis cell death modalities with TfR1 immunostaining

Determining cell death mechanisms occurring in patient and animal tissues is a longstanding goal that requires suitable biomarkers and accurate quantification. However, effective methods remain elusive. To develop more powerful and unbiased analytic frameworks, we developed a machine learning approach for automated cell death classification. Image sets were collected of HT-1080 fibrosarcoma cells undergoing ferroptosis or apoptosis and stained with an anti-transferrin receptor 1 (TfR1) antibody, together with nuclear and F-actin staining. Features were extracted using high-content-analysis software, and a classifier was constructed by fitting a multinomial logistic lasso regression model to the data. The prediction accuracy of the classifier within three classes (control, ferroptosis, apoptosis) was 93%. Thus, TfR1 staining, combined with nuclear and F-actin staining, can reliably detect both apoptotic and ferroptosis cells when cell features are analyzed in an unbiased manner using machine learning, providing a method for unbiased analysis of modes of cell death