Project description:Chromatin-organizing factors, like CTCF and cohesins, have been implicated in the control of complex viral regulatory programs. We investigated the role of CTCF and cohesin in the control of the latent to lytic switch for Kaposi's Sarcoma-Associated Herpesvirus (KSHV). We found that cohesin subunits, but not CTCF, were required for the repression of KSHV immediate early gene transcription. Depletion of cohesin subunits Rad21, SMC1, or SMC3 resulted in lytic cycle gene transcription and viral DNA replication. In contrast, depletion of CTCF failed to induce lytic transcription or DNA replication. ChiP-Seq analysis revealed that cohesins and CTCF bound to several sites within the immediate early control regions for ORF50 and more distal 5' sites that also regulate the divergently transcribed ORF45-46-47 gene cluster. Rad21 depletion led to a robust increase in ORF45 and ORF47 transcripts, with similar kinetics to that observed with chemical induction by sodium butyrate. During latency, the chromatin between the ORF45 and ORF50 transcription start sites was enriched in histone H3K4me3 with elevated H3K9ac at the ORF45 promoter and elevated H3K27me3 at the ORF50 promoter. A paused form of RNA pol II was loosely associated with the ORF45 promoter region during latency, but was converted to an active elongating form upon reactivation induced by Rad21 depletion. Butyrate-induced transcription of ORF45 and ORF47 was resistant to cyclohexamide, suggesting that these genes have immediate early features similar to ORF50. Butyrate-treatment caused the rapid dissociation of cohesins and loss of CTCF binding at the immediate early gene locus, suggesting that cohesins may be a direct target of butyrate-mediated lytic induction. Our findings implicate cohesins as a major repressor of KSHV lytic gene activation, and function coordinately with CTCF to regulate the switch between latent and lytic gene activity. Study of chromatin-organizing factors, like CTCF and cohesins.

Project description:Kaposi’s sarcoma-associated herpesvirus (KSHV) is the etiologic agent of primary effusion lymphoma (PEL). All PEL cell lines are infected with KSHV, and 70% are co-infected with Epstein-Barr Virus (EBV). KSHV reactivation from latency requires promoter-specific transactivation by the KSHV Rta protein through interactions with RBP-Jk (CSL), the cellular DNA binding component of the Notch signal transduction pathway. EBV transformation of primary B cells requires EBV nuclear antigen (EBNA)-2 to interact with RBP-Jk to direct the latent viral and cellular gene expression program. Although KSHV Rta and EBV EBNA-2 both require RBP-Jk for transactivation, previous studies have suggested that RBP-Jk-dependent transactivators do not function identically. We have found that the EBV latent protein LMP-1 is expressed in less than 5% of KSHV+/EBV+ PEL cells, but is induced in an Rta-dependent fashion when KSHV reactivates. KSHV Rta transactivates the EBV latency promoters in an RBP-Jk-dependent fashion and forms a ternary complex with RBP-Jk on the promoters. In B cells that are conditionally transformed by EBV alone, we show that KSHV Rta complements a short-term EBNA2 growth deficiency in an autocrine/paracrine manner. Complementaton of EBNA2-deficiency by Rta depends on RBP-Jk and LMP-1, and Rta transactivation is required for optimal growth of KSHV+/EBV+ PEL lines. Our data suggest that Rta can contribute to EBV-driven cellular growth by transactivating RBP-Jk-dependent EBV latency genes. However, our data also suggest that EBNA2 and Rta induce distinct alterations in the cellular proteomes that contribute to growth of infected cells. EREB2-5 cells were transfected and grown in the presence or absence of β-estradiol, as described. Seven days post-transfection, protein extracts were prepared, and 200 ugs. of each were analyzed using the RayBio Human Apoptosis Antibody Array Kit (RayBiotech) as per manufacturers suggestions. The membranes were exposed to autoradiography film for different times to detect the chemiluminescent signals. Images with signals in linear range were quantitated using the program ImageJ [59]. For each membrane, signals from the negative control spots were averaged, and then subtracted from each of the other spots. A signal was considered valid if its value exceeded both its average local background, and the average of all valid negative control values. Valid signals were normalized using the positive control spots (for cellular BID protein). Fold change in signals for each spot were quantitated by dividing by the valid signals for each corresponding spot on the minus β-estradiol membrane. Average fold change, and standard deviation, were calculated for each protein.

Project description:Purpose: We used RNA deep sequencing to characterize KSHV expression in a large collection of KS biopsies (n=41) from HIV-infected Ugandans. Using a novel approach to quantitate expression in complex genomes like KSHV, we found that RNA from a single KSHV promoter within the latency region constituted the majority of KSHV transcripts in the KS tumors. Alternate RNA processing produced different spliced and un-spliced transcripts with different coding potentials. Differential expression of other KSHV genes was detected which segregated the tumors into three different types depending on their expression of lytic or latency genes. Quantitative analysis of KSHV expression in KS tumors provides an important basis for future studies on the role of KSHV in the development of KS Methods: Total nucleic acids were extracted using RLT buffer (Qiagen) and then RNA was isolated using the RNeasy mini kit with DNAse treatment step. Total RNA integrity was checked using an Agilent 2200 TapeStation (Agilent Technologies, Inc., Santa Clara, CA) and quantified using a Trinean DropSense96 spectrophotometer (Caliper Life Sciences, Hopkinton, MA). Unstranded RNA-seq libraries were prepared from 300 ng of total RNA using the TruSeq RNA Sample Prep Kit v2 (Illumina, Inc., San Diego, CA, USA). Four KS tumors libraries were prepared using the TruSeq Stranded mRNA Library Kit (Illumina) from 100 ng of total RNA. Library size distributions were validated using an Agilent 2200 TapeStation (Agilent Technologies, Santa Clara, CA, USA). Additional library QC, pooling of indexed libraries, and cluster optimization was performed using Life Technologies’ Invitrogen Qubit® 2.0 Fluorometer (Life Technologies-Invitrogen, Carlsbad, CA, USA). The unstranded RNA-seq libraries were pooled (5-plex) and the stranded libraries were pooled (4-plex) and each pool was clustered onto a flow cell lane. Sequencing was performed using an Illumina HiSeq 2500 in “High Output” mode with a paired-end, 50 base reads (PE50) sequencing strategy for the unstranded libraries and non-paired end for the stranded libraries. Image analysis and base calling was performed using Illumina's Real Time Analysis v1.18 software, followed by 'demultiplexing' of indexed reads and generation of FASTQ files, using Illumina's bcl2fastq Conversion Software v1.8.2. Analysis: Low-quality reads were removed prior to alignment to the KSHV (aka HHV-8) reference sequence (accession number NC_009333 for the KSHV GK18 strain) using TopHat2 (version 2.0.14) in a local instance of Galaxy. For quantitation purposes, the reads from paired-end libraries (non-stranded) were analyzed as unpaired (single-end data) to allow each read of the pair to map unambiguously to a single gene feature. The reads from both strands of the stranded libraries (non-paired end) were either concatenated and analyzed together (librarytype=unstranded) for comparison to the non-stranded paired end libraries or were analyzed separately (librarytype=FR) to show strand specificity. TopHat2 was used to detect splicing events ab initio. The default presets were used except that the maximum intron length was decreased to 10,000 and the maximum number of alignments allowed was decreased from 20 to 1, to avoid overcounting reads to repetitive regions. HTSeq (version 0.6) was used to quantitate the reads mapping to the unique set of UCDS gene features within the novel revised gene feature file "KSHV NC_009333 UCDS ver 121715.gff". The “intersection (non-empty)” setting in HTSeq was used to count all reads mapping completely or partially to a UCDS feature to maximize read count (featuretype=UCDS; IDattribute=gene). No reads were eliminated by ambiguity since the UCDS features were 50 bp apart, the length of a read. The read count was expressed as transcripts per million (TPM) by first normalizing the read count to reads per kilobase (RPK) by dividing the read counts by the length of the UCDS gene feature, in kilobases. The “per million” scaling factor was determined by summing all of the RPK values in a sample and dividing by 1,000,000. Each RPK value was then divided by the “per million” scaling factor to give TPM of mapped KSHV reads. Hierarchical clustering of TPM normalized expression levels was performed using the algorithm implemented in CIMminer. Hierarchical clustering of the gene correlation matrix was performed by calculating the Pearson correlation between the normalized transcript levels (TPM) associated with each pair of UCDS gene features, using a script in R to create and output the correlation matrix. Shiny web applications were developed for R-based principal component analysis (available at https://efg-ds.shinyapps.io/pcaApp/) and boxplot analysis of gene expression levels (available at https://efg-ds.shinyapps.io/boxplotApp/). Conclusions: We have used RNAseq to analyze and quantitate KSHV gene expression in a large collection of 41 KS tumor biopsies from HIV-infected individuals in Uganda that were naïve to ART. The RNAseq libraries were sequenced to an average depth of 100 million reads yielding up to 159,000 KSHV-mapped reads, and RNA reads mapping to non-overlapping UCDS features were quantitated using the new UCDS gene feature file. Phylogenetic analysis of the complete ORF75 sequence revealed the presence of at least six different KSHV strains in these tumor samples. We identified a set of transcripts from the latency region at the right end of the genome that was highly and consistently expressed in all the KS tumors. Variable expression of genes involved with transcription regulation and immune modulation was observed, with minimal expression of genes involved with viral replication, virion structure, or assembly. No correlation was observed between the KSHV transcript patterns detected in macular, nodular or fungating KS lesions. In contrast, the transcript patterns of different tumor lesions from the same individual showed the most similarity regardless of the tumor morphotype.

Project description:Herpesvirus latency is generally thought to be governed by epigenetic modifications, but the dynamics of viral chromatin at early timepoints of latent infection are poorly understood. Here, we report a comprehensive spatial and temporal analysis of epigenetic modifications during latent infection with Kaposi's sarcoma associated herpesvirus (KSHV), the etiologic agent of Kaposi's sarcoma and primary effusion lymphoma (PEL). Using high resolution tiling microarrays in conjunction with immunprecipitation of methylated DNA (MeDIP) and modified histones (ChIP), we have determined global patterns of epigenetic modifications across the KSHV genome in several tumor-derived cell lines as well as de novo infected endothelial cells, revealing highly distinct landscapes of epigenetic modifications associated with latent KSHV infection. We find that KSHV genomes are subject to profound methylation at CpG dinucleotides, leading to the establishment of characteristic global DNA methylation patterns. However, such patterns evolved slowly and thus are unlikely to govern latency early during the infection process. In contrast, we observed that latent histone modification patterns were rapidly established upon a de novo infection. Our analysis furthermore demonstrates that such patterns are not characterized by the absence of activating histone modifications, since both H3K9/K14-ac and H3K4-me3 marks were prominently detected at several loci, including the promoter of the lytic cycle transactivator Rta. While these regions were furthermore largely devoid of the constitutive heterochromatin marker H3K9-me3, we observed rapid and widespread deposition of H3K27-me3 across latent KSHV genomes, a bivalent modification which is able to repress transcription despite of the simultaneous presence of activating marks. Our findings suggest that the epigenetic patterns identified here induce a poised state of repression during viral latency, which can be rapidly reversed once the lytic cycle is induced. This dataset contains our ChIP-on-chip data; the MeDIP data are deposited in a separate dataset.

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Cohesins Repress KSHV Immediate Early Gene Transcription During Latency

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