Histone deacetylase inhibitors induce complex host responses that contribute to differential potencies of these compounds in HIV reactivation.

Histone deacetylase (HDAC) inhibitors (HDACis) have been widely tested in clinical trials for their ability to reverse HIV latency but have yielded only limited success. One HDACi, suberoylanilide hydroxamic acid (SAHA), exhibits off-target effects on host gene expression predicted to interfere with induction of HIV transcription. Romidepsin (RMD) has higher potency and specificity for class I HDACs implicated in maintaining HIV provirus in the latent state. More robust HIV reactivation has indeed been achieved with RMD use ex vivo than with SAHA; however, reduction of viral reservoir size has not been observed in clinical trials. Therefore, using RNA-Seq, we sought to compare the effects of SAHA and RMD on gene expression in primary CD4+ T cells. Among the genes whose expression was modulated by both HDACi agents, we identified genes previously implicated in HIV latency. Two genes, SMARCB1 and PARP1, whose modulation by SAHA and RMD is predicted to inhibit HIV reactivation, were evaluated in the major maturation subsets of CD4+ T cells and were consistently either up- or down-regulated by both HDACi compounds. Our results indicate that despite having different potencies and HDAC specificities, SAHA and RMD modulate an overlapping set of genes, implicated in HIV latency regulation. Some of these genes merit exploration as additional targets to improve the therapeutic outcomes of "shock and kill" strategies. The overall complexity of HDACi-induced responses among host genes with predicted stimulatory or inhibitory effects on HIV expression likely contributes to differential HDACi potencies and dictates the outcome of HIV reactivation.

Cis-regulatory control of transcriptional timing and noise in response to estrogen.

Cis-regulatory elements control transcription levels, temporal dynamics, and cell-cell variation or transcriptional noise. However, the combination of regulatory features that control these different attributes is not fully understood. Here, we used single cell RNA-seq during an estrogen treatment time course and machine learning to identify predictors of expression timing and noise. We find that genes with multiple active enhancers exhibit faster temporal responses. We verified this finding by showing that manipulation of enhancer activity changes the temporal response of estrogen target genes. Analysis of transcriptional noise uncovered a relationship between promoter and enhancer activity, with active promoters associated with low noise and active enhancers linked to high noise. Finally, we observed that co-expression across single cells is an emergent property associated with chromatin looping, timing, and noise. Overall, our results indicate a fundamental tradeoff between a gene's ability to quickly respond to incoming signals and maintain low variation across cells.

Estrogen-induced chromatin looping changes identify a subset of functional regulatory elements.

Transcriptional enhancers can regulate individual or multiple genes through long-range three-dimensional (3D) genome interactions, and these interactions are commonly altered in cancer. Yet, the functional relationship between changes in 3D interactions associated with regulatory regions and differential gene expression appears context-dependent. In this study, we used HiChiP to capture changes in 3D genome interactions between active regulatory regions of endometrial cancer cells in response to estrogen treatment and uncovered significant differential long-range interactions that are strongly enriched for estrogen receptor α (ER) bound sites (ERBS). The ERBS anchoring differential loops with either a gene's promoter or distal regions were correlated with larger transcriptional responses to estrogen compared to ERBS not involved in differential interactions. To functionally test this observation, CRISPR-based Enhancer-i was used to deactivate specific ERBS, which revealed a wide range of effects on the transcriptional response to estrogen. However, these effects are only subtly and not significantly stronger for ERBS in differential loops. In addition, we observed an enrichment of 3D interactions between the promoters of estrogen up-regulated genes and found that looped promoters can work together cooperatively. Overall, our work suggests that changes in 3D genome structure upon estrogen treatment identify some functionally important regulatory regions; however, these changes aren't required for a transcriptional response to E2 in endometrial cancer cells.

Cis-regulatory control of transcriptional timing and noise in response to estrogen.

Cis-regulatory elements control transcription levels, temporal dynamics, and cell-cell variation or transcriptional noise. However, the combination of regulatory features that control these different attributes is not fully understood. Here, we used single-cell RNA-seq during an estrogen treatment time course and machine learning to identify predictors of expression timing and noise. We found that genes with multiple active enhancers exhibit faster temporal responses. We verified this finding by showing that manipulation of enhancer activity changes the temporal response of estrogen target genes. Analysis of transcriptional noise uncovered a relationship between promoter and enhancer activity, with active promoters associated with low noise and active enhancers linked to high noise. Finally, we observed that co-expression across single cells is an emergent property associated with chromatin looping, timing, and noise. Overall, our results indicate a fundamental tradeoff between a gene's ability to quickly respond to incoming signals and maintain low variation across cells.

Oct1 cooperates with the Smad family of transcription factors to promote mesodermal lineage specification.

The transition between pluripotent and tissue-specific states is a key aspect of development. Understanding the pathways driving these transitions will facilitate the engineering of properly differentiated cells for experimental and therapeutic uses. Here, we showed that during mesoderm differentiation, the transcription factor Oct1 activated developmental lineage-appropriate genes that were silent in pluripotent cells. Using mouse embryonic stem cells (ESCs) with an inducible knockout of Oct1, we showed that Oct1 deficiency resulted in poor induction of mesoderm-specific genes, leading to impaired mesodermal and terminal muscle differentiation. Oct1-deficient cells exhibited poor temporal coordination of the induction of lineage-specific genes and showed inappropriate developmental lineage branching, resulting in poorly differentiated cell states retaining epithelial characteristics. In ESCs, Oct1 localized with the pluripotency factor Oct4 at mesoderm-associated genes and remained bound to those loci during differentiation after the dissociation of Oct4. Binding events for Oct1 overlapped with those for the histone lysine demethylase Utx, and an interaction between Oct1 and Utx suggested that these two proteins cooperate to activate gene expression. The specificity of the ubiquitous Oct1 for the induction of mesodermal genes could be partially explained by the frequent coexistence of Smad and Oct binding sites at mesoderm-specific genes and the cooperative stimulation of mesodermal gene transcription by Oct1 and Smad3. Together, these results identify Oct1 as a key mediator of mesoderm lineage-specific gene induction.

Use of GapmeRs for gene expression knockdowns in human primary resting CD4+ T cells.

Human primary resting CD4+ T cells are difficult to transfect while preserving viability. The present study evaluated gymnotic delivery and RNase H1-dependent gene expression knockdown mediated by antisense oligonucleotides, called GapmeRs. Exposure of primary resting CD4+ T cells to GapmeRs did not cause cell activation or affect cell viability. Gene expression knockdowns were stable at least up to 48 h after removal of GapmeRs from culture. Exposure to GapmeRs resulted in comparable levels of degradation along the entire transcript, which could be important when studying function of regulatory long non-coding RNAs. Efficiency of transcript degradation was not solely dependent on the dose of GapmeR, RNA target and its localization. When using GapmeRs, some optimization is required, and all targets have to be individually tested; however, using GapmeRs is advantageous in experiments where preservation of the resting state of the human primary CD4+ T cells and targeting nuclear RNAs are desired. In certain cases, combining GapmeR with siRNA for the same target may improve knockdown efficiency.