Genome-scale chromatin binding dynamics of RNA Polymerase II general transcription machinery components.

A great deal of work has revealed, in structural detail, the components of the preinitiation complex (PIC) machinery required for initiation of mRNA gene transcription by RNA polymerase II (Pol II). However, less-well understood are the in vivo PIC assembly pathways and their kinetics, an understanding of which is vital for determining how rates of in vivo RNA synthesis are established. We used competition ChIP in budding yeast to obtain genome-scale estimates of the residence times for five general transcription factors (GTFs): TBP, TFIIA, TFIIB, TFIIE and TFIIF. While many GTF-chromatin interactions were short-lived ( < 1 min), there were numerous interactions with residence times in the range of several minutes. Sets of genes with a shared function also shared similar patterns of GTF kinetic behavior. TFIIE, a GTF that enters the PIC late in the assembly process, had residence times correlated with RNA synthesis rates. The datasets and results reported here provide kinetic information for most of the Pol II-driven genes in this organism, offering a rich resource for exploring the mechanistic relationships between PIC assembly, gene regulation, and transcription.

Novel Mouse Model of Myocardial Infarction, Plaque Rupture, and Stroke Shows Improved Survival With Myeloperoxidase Inhibition.

BACKGROUND: Thromboembolic events, including myocardial infarction (MI) or stroke, caused by the rupture or erosion of unstable atherosclerotic plaques are the leading cause of death worldwide. Although most mouse models of atherosclerosis develop lesions in the aorta and carotid arteries, they do not develop advanced coronary artery lesions. Moreover, they do not undergo spontaneous plaque rupture with MI and stroke or do so at such a low frequency that they are not viable experimental models to study late-stage thrombotic events or to identify novel therapeutic approaches for treating atherosclerotic disease. This has stymied the development of more effective therapeutic approaches for reducing these events beyond what has been achieved with aggressive lipid lowering. Here, we describe a diet-inducible mouse model that develops widespread advanced atherosclerosis in coronary, brachiocephalic, and carotid arteries with plaque rupture, MI, and stroke. METHODS: We characterized a novel mouse model with a C-terminal mutation in the scavenger receptor class B, type 1 (SR-BI), combined with Ldlr knockout (designated SR-BI∆CT/∆CT/Ldlr-/-). Mice were fed Western diet (WD) for 26 weeks and analyzed for MI and stroke. Coronary, brachiocephalic, and carotid arteries were analyzed for atherosclerotic lesions and indices of plaque stability. To validate the utility of this model, SR-BI∆CT/∆CT/Ldlr-/- mice were treated with the drug candidate AZM198, which inhibits myeloperoxidase, an enzyme produced by activated neutrophils that predicts rupture of human atherosclerotic lesions. RESULTS: SR-BI∆CT/∆CT/Ldlr-/- mice show high (>80%) mortality rates after 26 weeks of WD feeding because of major adverse cardiovascular events, including spontaneous plaque rupture with MI and stroke. Moreover, WD-fed SR-BI∆CT/∆CT/Ldlr-/- mice displayed elevated circulating high-sensitivity cardiac troponin I and increased neutrophil extracellular trap formation within lesions compared with control mice. Treatment of WD-fed SR-BI∆CT/∆CT/Ldlr-/- mice with AZM198 showed remarkable benefits, including >90% improvement in survival and >60% decrease in the incidence of plaque rupture, MI, and stroke, in conjunction with decreased circulating high-sensitivity cardiac troponin I and reduced neutrophil extracellular trap formation within lesions. CONCLUSIONS: WD-fed SR-BI∆CT/∆CT/Ldlr-/- mice more closely replicate late-stage clinical events of advanced human atherosclerotic disease than previous models and can be used to identify and test potential new therapeutic agents to prevent major adverse cardiac events.

DeepGSEA: explainable deep gene set enrichment analysis for single-cell transcriptomic data.

MOTIVATION: Gene set enrichment (GSE) analysis allows for an interpretation of gene expression through pre-defined gene set databases and is a critical step in understanding different phenotypes. With the rapid development of single-cell RNA sequencing (scRNA-seq) technology, GSE analysis can be performed on fine-grained gene expression data to gain a nuanced understanding of phenotypes of interest. However, with the cellular heterogeneity in single-cell gene profiles, current statistical GSE analysis methods sometimes fail to identify enriched gene sets. Meanwhile, deep learning has gained traction in applications like clustering and trajectory inference in single-cell studies due to its prowess in capturing complex data patterns. However, its use in GSE analysis remains limited, due to interpretability challenges. RESULTS: In this paper, we present DeepGSEA, an explainable deep gene set enrichment analysis approach which leverages the expressiveness of interpretable, prototype-based neural networks to provide an in-depth analysis of GSE. DeepGSEA learns the ability to capture GSE information through our designed classification tasks, and significance tests can be performed on each gene set, enabling the identification of enriched sets. The underlying distribution of a gene set learned by DeepGSEA can be explicitly visualized using the encoded cell and cellular prototype embeddings. We demonstrate the performance of DeepGSEA over commonly used GSE analysis methods by examining their sensitivity and specificity with four simulation studies. In addition, we test our model on three real scRNA-seq datasets and illustrate the interpretability of DeepGSEA by showing how its results can be explained. AVAILABILITY AND IMPLEMENTATION: https://github.com/Teddy-XiongGZ/DeepGSEA.

ProtoCell4P: an explainable prototype-based neural network for patient classification using single-cell RNA-seq.

MOTIVATION: The rapid advance in single-cell RNA sequencing (scRNA-seq) technology over the past decade has provided a rich resource of gene expression profiles of single cells measured on patients, facilitating the study of many biological questions at the single-cell level. One intriguing research is to study the single cells which play critical roles in the phenotypes of patients, which has the potential to identify those cells and genes driving the disease phenotypes. To this end, deep learning models are expected to well encode the single-cell information and achieve precise prediction of patients' phenotypes using scRNA-seq data. However, we are facing critical challenges in designing deep learning models for classifying patient samples due to (i) the samples collected in the same dataset contain a variable number of cells-some samples might only have hundreds of cells sequenced while others could have thousands of cells, and (ii) the number of samples available is typically small and the expression profile of each cell is noisy and extremely high-dimensional. Moreover, the black-box nature of existing deep learning models makes it difficult for the researchers to interpret the models and extract useful knowledge from them. RESULTS: We propose a prototype-based and cell-informed model for patient phenotype classification, termed ProtoCell4P, that can alleviate problems of the sample scarcity and the diverse number of cells by leveraging the cell knowledge with representatives of cells (called prototypes), and precisely classify the patients by adaptively incorporating information from different cells. Moreover, this classification process can be explicitly interpreted by identifying the key cells for decision making and by further summarizing the knowledge of cell types to unravel the biological nature of the classification. Our approach is explainable at the single-cell resolution which can identify the key cells in each patient's classification. The experimental results demonstrate that our proposed method can effectively deal with patient classifications using single-cell data and outperforms the existing approaches. Furthermore, our approach is able to uncover the association between cell types and biological classes of interest from a data-driven perspective. AVAILABILITY AND IMPLEMENTATION: https://github.com/Teddy-XiongGZ/ProtoCell4P.

Interpretable meta-learning of multi-omics data for survival analysis and pathway enrichment.

MOTIVATION: Despite the success of recent machine learning algorithms' applications to survival analysis, their black-box nature hinders interpretability, which is arguably the most important aspect. Similarly, multi-omics data integration for survival analysis is often constrained by the underlying relationships and correlations that are rarely well understood. The goal of this work is to alleviate the interpretability problem in machine learning approaches for survival analysis and also demonstrate how multi-omics data integration improves survival analysis and pathway enrichment. We use meta-learning, a machine-learning algorithm that is trained on a variety of related datasets and allows quick adaptations to new tasks, to perform survival analysis and pathway enrichment on pan-cancer datasets. In recent machine learning research, meta-learning has been effectively used for knowledge transfer among multiple related datasets. RESULTS: We use meta-learning with Cox hazard loss to show that the integration of TCGA pan-cancer data increases the performance of survival analysis. We also apply advanced model interpretability method called DeepLIFT (Deep Learning Important FeaTures) to show different sets of enriched pathways for multi-omics and transcriptomics data. Our results show that multi-omics cancer survival analysis enhances performance compared with using transcriptomics or clinical data alone. Additionally, we show a correlation between variable importance assignment from DeepLIFT and gene coenrichment, suggesting that genes with higher and similar contribution scores are more likely to be enriched together in the same enrichment sets. AVAILABILITY AND IMPLEMENTATION: https://github.com/berkuva/TCGA-omics-integration.

Inhibition of DYRK1a Enhances Cardiomyocyte Cycling After Myocardial Infarction.

BACKGROUND: DYRK1a (dual-specificity tyrosine phosphorylation-regulated kinase 1a) contributes to the control of cycling cells, including cardiomyocytes. However, the effects of inhibition of DYRK1a on cardiac function and cycling cardiomyocytes after myocardial infarction (MI) remain unknown. METHODS: We investigated the impacts of pharmacological inhibition and conditional genetic ablation of DYRK1a on endogenous cardiomyocyte cycling and left ventricular systolic function in ischemia-reperfusion (I/R) MI using αMHC-MerDreMer-Ki67p-RoxedCre::Rox-Lox-tdTomato-eGFP (RLTG) (denoted αDKRC::RLTG) and αMHC-Cre::Fucci2aR::DYRK1aflox/flox mice. RESULTS: We observed that harmine, an inhibitor of DYRK1a, improved left ventricular ejection fraction (39.5±1.6% and 29.1±1.6%, harmine versus placebo, respectively), 2 weeks after I/R MI. Harmine also increased cardiomyocyte cycling after I/R MI in αDKRC::RLTG mice, 10.8±1.5 versus 24.3±2.6 enhanced Green Fluorescent Protein (eGFP)+ cardiomyocytes, placebo versus harmine, respectively, P=1.0×10-3. The effects of harmine on left ventricular ejection fraction were attenuated in αDKRC::DTA mice that expressed an inducible diphtheria toxin in adult cycling cardiomyocytes. The conditional cardiomyocyte-specific genetic ablation of DYRK1a in αMHC-Cre::Fucci2aR::DYRK1aflox/flox (denoted DYRK1a k/o) mice caused cardiomyocyte hyperplasia at baseline (210±28 versus 126±5 cardiomyocytes per 40× field, DYRK1a k/o versus controls, respectively, P=1.7×10-2) without changes in cardiac function compared with controls, or compensatory changes in the expression of other DYRK isoforms. After I/R MI, DYRK1a k/o mice had improved left ventricular function (left ventricular ejection fraction 41.8±2.2% and 26.4±0.8%, DYRK1a k/o versus control, respectively, P=3.7×10-2). RNAseq of cardiomyocytes isolated from αMHC-Cre::Fucci2aR::DYRK1aflox/flox and αMHC-Cre::Fucci2aR mice after I/R MI or Sham surgeries identified enrichment in mitotic cell cycle genes in αMHC-Cre::Fucci2aR::DYRK1aflox/flox compared with αMHC-Cre::Fucci2aR. CONCLUSIONS: The pharmacological inhibition or cardiomyocyte-specific ablation of DYRK1a caused baseline hyperplasia and improved cardiac function after I/R MI, with an increase in cell cycle gene expression, suggesting the inhibition of DYRK1a may serve as a therapeutic target to treat MI.

A Step Toward Personalized Surgical Decision Making: Machine Learning Predicts 1 Versus Numerous Melanoma Lymph Node Metastases Using RNA-sequencing.

OBJECTIVE: Develop a predictive model to identify patients with 1 pathologic lymph node (pLN) versus >1 pLN using machine learning applied to gene expression profiles and clinical data as input variables. BACKGROUND: Standard management for clinically detected melanoma lymph node metastases is complete therapeutic LN dissection (TLND). However, >40% of patients with a clinically detected melanoma lymph node will only have 1 pLN on final review. Recent data suggest that targeted excision of just the single enlarged LN may provide excellent regional control, with less morbidity than TLND. The selection of patients for less morbid surgery requires accurate identification of those with only 1 pLN. METHODS: The Cancer Genome Atlas database was used to identify patients who underwent TLND for melanoma. Pathology reports in The Cancer Genome Atlas were reviewed to identify the number of pLNs. Patients were included for machine learning analyses if RNA sequencing data were available from a pLN. After feature selection, the top 20 gene expression and clinical input features were used to train a ridge logistic regression model to predict patients with 1 pLN versus >1 pLN using 10-fold cross-validation on 80% of samples. The model was then tested on the remaining holdout samples. RESULTS: A total of 153 patients met inclusion criteria: 64 with one pLN (42%) and 89 with >1 pLNs (58%). Feature selection identified 1 clinical (extranodal extension) and 19 gene expression variables used to predict patients with 1 pLN versus >1 pLN. The ridge logistic regression model identified patient groups with an accuracy of 90% and an area under the receiver operating characteristic curve of 0.97. CONCLUSIONS: Gene expression profiles together with clinical variables can distinguish melanoma metastasis patients with 1 pLN versus >1 pLN. Future models trained using positron emission tomography/computed tomography imaging, gene expression, and relevant clinical variables may further improve accuracy and may predict patients who can be managed with a targeted LN excision rather than a complete TLND.

A Sir2-regulated locus control region in the recombination enhancer of Saccharomyces cerevisiae specifies chromosome III structure.

The NAD+-dependent histone deacetylase Sir2 was originally identified in Saccharomyces cerevisiae as a silencing factor for HML and HMR, the heterochromatic cassettes utilized as donor templates during mating-type switching. MATa cells preferentially switch to MATα using HML as the donor, which is driven by an adjacent cis-acting element called the recombination enhancer (RE). In this study we demonstrate that Sir2 and the condensin complex are recruited to the RE exclusively in MATa cells, specifically to the promoter of a small gene within the right half of the RE known as RDT1. We also provide evidence that the RDT1 promoter functions as a locus control region (LCR) that regulates both transcription and long-range chromatin interactions. Sir2 represses RDT1 transcription until it is removed from the promoter in response to a dsDNA break at the MAT locus induced by HO endonuclease during mating-type switching. Condensin is also recruited to the RDT1 promoter and is displaced upon HO induction, but does not significantly repress RDT1 transcription. Instead condensin appears to promote mating-type donor preference by maintaining proper chromosome III architecture, which is defined by the interaction of HML with the right arm of chromosome III, including MATa and HMR. Remarkably, eliminating Sir2 and condensin recruitment to the RDT1 promoter disrupts this structure and reveals an aberrant interaction between MATa and HMR, consistent with the partially defective donor preference for this mutant. Global condensin subunit depletion also impairs mating-type switching efficiency and donor preference, suggesting that modulation of chromosome architecture plays a significant role in controlling mating-type switching, thus providing a novel model for dissecting condensin function in vivo.

Pausing sites of RNA polymerase II on actively transcribed genes are enriched in DNA double-stranded breaks.

DNA double-stranded breaks (DSBs) are strongly associated with active transcription, and promoter-proximal pausing of RNA polymerase II (Pol II) is a critical step in transcriptional regulation. Mapping the distribution of DSBs along actively expressed genes and identifying the location of DSBs relative to pausing sites can provide mechanistic insights into transcriptional regulation. Using genome-wide DNA break mapping/sequencing techniques at single-nucleotide resolution in human cells, we found that DSBs are preferentially located around transcription start sites of highly transcribed and paused genes and that Pol II promoter-proximal pausing sites are enriched in DSBs. We observed that DSB frequency at pausing sites increases as the strength of pausing increases, regardless of whether the pausing sites are near or far from annotated transcription start sites. Inhibition of topoisomerase I and II by camptothecin and etoposide treatment, respectively, increased DSBs at the pausing sites as the concentrations of drugs increased, demonstrating the involvement of topoisomerases in DSB generation at the pausing sites. DNA breaks generated by topoisomerases are short-lived because of the religation activity of these enzymes, which these drugs inhibit; therefore, the observation of increased DSBs with increasing drug doses at pausing sites indicated active recruitment of topoisomerases to these sites. Furthermore, the enrichment and locations of DSBs at pausing sites were shared among different cell types, suggesting that Pol II promoter-proximal pausing is a common regulatory mechanism. Our findings support a model in which topoisomerases participate in Pol II promoter-proximal pausing and indicated that DSBs at pausing sites contribute to transcriptional activation.

Stem Cell Pluripotency Genes Klf4 and Oct4 Regulate Complex SMC Phenotypic Changes Critical in Late-Stage Atherosclerotic Lesion Pathogenesis.

BACKGROUND: Rupture and erosion of advanced atherosclerotic lesions with a resultant myocardial infarction or stroke are the leading worldwide cause of death. However, we have a limited understanding of the identity, origin, and function of many cells that make up late-stage atherosclerotic lesions, as well as the mechanisms by which they control plaque stability. METHODS: We conducted a comprehensive single-cell RNA sequencing of advanced human carotid endarterectomy samples and compared these with single-cell RNA sequencing from murine microdissected advanced atherosclerotic lesions with smooth muscle cell (SMC) and endothelial lineage tracing to survey all plaque cell types and rigorously determine their origin. We further used chromatin immunoprecipitation sequencing (ChIP-seq), bulk RNA sequencing, and an innovative dual lineage tracing mouse to understand the mechanism by which SMC phenotypic transitions affect lesion pathogenesis. RESULTS: We provide evidence that SMC-specific Klf4- versus Oct4-knockout showed virtually opposite genomic signatures, and their putative target genes play an important role regulating SMC phenotypic changes. Single-cell RNA sequencing revealed remarkable similarity of transcriptomic clusters between mouse and human lesions and extensive plasticity of SMC- and endothelial cell-derived cells including 7 distinct clusters, most negative for traditional markers. In particular, SMC contributed to a Myh11-, Lgals3+ population with a chondrocyte-like gene signature that was markedly reduced with SMC-Klf4 knockout. We observed that SMCs that activate Lgals3 compose up to two thirds of all SMC in lesions. However, initial activation of Lgals3 in these cells does not represent conversion to a terminally differentiated state, but rather represents transition of these cells to a unique stem cell marker gene-positive, extracellular matrix-remodeling, "pioneer" cell phenotype that is the first to invest within lesions and subsequently gives rise to at least 3 other SMC phenotypes within advanced lesions, including Klf4-dependent osteogenic phenotypes likely to contribute to plaque calcification and plaque destabilization. CONCLUSIONS: Taken together, these results provide evidence that SMC-derived cells within advanced mouse and human atherosclerotic lesions exhibit far greater phenotypic plasticity than generally believed, with Klf4 regulating transition to multiple phenotypes including Lgals3+ osteogenic cells likely to be detrimental for late-stage atherosclerosis plaque pathogenesis.

Associations of immune cell homing gene signatures and infiltrates of lymphocyte subsets in human melanomas: discordance with CD163+ myeloid cell infiltrates.

BACKGROUND: Immune cells in the tumor microenvironment have prognostic value. In preclinical models, recruitment and infiltration of these cells depends on immune cell homing (ICH) genes such as chemokines, cell adhesion molecules, and integrins. We hypothesized ICH ligands CXCL9-11 and CCL2-5 would be associated with intratumoral T-cells, while CXCL13 would be more associated with B-cell infiltrates. METHODS: Samples of human melanoma were submitted for gene expression analysis and immune cells identified by immunohistochemistry. Associations between the two were evaluated with unsupervised hierarchical clustering using correlation matrices from Spearman rank tests. Univariate analysis performed Mann-Whitney tests. RESULTS: For 119 melanoma specimens, analysis of 78 ICH genes revealed association among genes with nonspecific increase of multiple immune cell subsets: CD45+, CD8+ and CD4+ T-cells, CD20+ B-cells, CD138+ plasma cells, and CD56+ NK-cells. ICH genes most associated with these infiltrates included ITGB2, ITGAL, CCL19, CXCL13, plus receptor/ligand pairs CXCL9 and CXCL10 with CXCR3; CCL4 and CCL5 with CCR5. This top ICH gene expression signature was also associated with genes representing immune-activation and effector function. In contrast, CD163+ M2-macrophages was weakly associated with a different ICH gene signature. CONCLUSION: These data do not support our hypothesis that each immune cell subset is uniquely associated with specific ICH genes. Instead, a larger set of ICH genes identifies melanomas with concordant infiltration of B-cell and T-cell lineages, while CD163+ M2-macrophage infiltration suggesting alternate mechanisms for their recruitment. Future studies should explore the extent ICH gene signature contributes to tertiary lymphoid structures or cross-talk between homing pathways.

Histone H3 lysine 4 methylation signature associated with human undernutrition.

Chronically undernourished children become stunted during their first 2 years and thereafter bear burdens of ill health for the rest of their lives. Contributors to stunting include poor nutrition and exposure to pathogens, and parental history may also play a role. However, the epigenetic impact of a poor environment on young children is largely unknown. Here we show the unfolding pattern of histone H3 lysine 4 trimethylation (H3K4me3) in children and mothers living in an urban slum in Dhaka, Bangladesh. A pattern of chromatin modification in blood cells of stunted children emerges over time and involves a global decrease in methylation at canonical locations near gene start sites and increased methylation at ectopic sites throughout the genome. This redistribution occurs at metabolic and immune genes and was specific for H3K4me3, as it was not observed for histone H3 lysine 27 acetylation in the same samples. Methylation changes in stunting globally resemble changes that occur in vitro in response to altered methylation capacity, suggesting that reduced levels of one-carbon nutrients in the diet play a key role in stunting in this population. A network of differentially expressed genes in stunted children reveals effects on chromatin modification machinery, including turnover of H3K4me3, as well as posttranscriptional gene regulation affecting immune response pathways and lipid metabolism. Consistent with these changes, reduced expression of the endocytic receptor gene LDL receptor 1 (LRP1) is a driver of stunting in a mouse model, suggesting a target for intervention.

Transcriptomes of six mutants in the Sen1 pathway reveal combinatorial control of transcription termination across the Saccharomyces cerevisiae genome.

Transcriptome studies on eukaryotic cells have revealed an unexpected abundance and diversity of noncoding RNAs synthesized by RNA polymerase II (Pol II), some of which influence the expression of protein-coding genes. Yet, much less is known about biogenesis of Pol II non-coding RNA than mRNAs. In the budding yeast Saccharomyces cerevisiae, initiation of non-coding transcripts by Pol II appears to be similar to that of mRNAs, but a distinct pathway is utilized for termination of most non-coding RNAs: the Sen1-dependent or "NNS" pathway. Here, we examine the effect on the S. cerevisiae transcriptome of conditional mutations in the genes encoding six different essential proteins that influence Sen1-dependent termination: Sen1, Nrd1, Nab3, Ssu72, Rpb11, and Hrp1. We observe surprisingly diverse effects on transcript abundance for the different proteins that cannot be explained simply by differing severity of the mutations. Rather, we infer from our results that termination of Pol II transcription of non-coding RNA genes is subject to complex combinatorial control that likely involves proteins beyond those studied here. Furthermore, we identify new targets and functions of Sen1-dependent termination, including a role in repression of meiotic genes in vegetative cells. In combination with other recent whole-genome studies on termination of non-coding RNAs, our results provide promising directions for further investigation.

High-content phenotypic assay for proliferation of human iPSC-derived cardiomyocytes identifies L-type calcium channels as targets.

Over 5 million people in the United States suffer from heart failure, due to the limited ability to regenerate functional cardiac tissue. One potential therapeutic strategy is to enhance proliferation of resident cardiomyocytes. However, phenotypic screening for therapeutic agents is challenged by the limited ability of conventional markers to discriminate between cardiomyocyte proliferation and endoreplication (e.g. polyploidy and multinucleation). Here, we developed a novel assay that combines automated live-cell microscopy and image processing algorithms to discriminate between proliferation and endoreplication by quantifying changes in the number of nuclei, changes in the number of cells, binucleation, and nuclear DNA content. We applied this assay to further prioritize hits from a primary screen for DNA synthesis, identifying 30 compounds that enhance proliferation of human induced pluripotent stem cell-derived cardiomyocytes. Among the most active compounds from the phenotypic screen are clinically approved L-type calcium channel blockers from multiple chemical classes whose activities were confirmed across different sources of human induced pluripotent stem cell-derived cardiomyocytes. Identification of compounds that stimulate human cardiomyocyte proliferation may provide new therapeutic strategies for heart failure.

HIV-1 Rev interacts with HERV-K RcREs present in the human genome and promotes export of unspliced HERV-K proviral RNA.

BACKGROUND: The HERV-K (HML-2) viruses are the youngest of the human endogenous retroviruses. They are present as several almost complete proviral copies and numerous fragments in the human genome. Many HERV-K proviruses express a regulatory protein Rec, which binds to an element present in HERV-K mRNAs called the RcRE. This interaction is necessary for the nucleo-cytoplasmic export and expression of HERV-K mRNAs that retain introns and plays a role analogous to that of Rev and the RRE in HIV replication. There are over 900 HERV-K RcREs distributed throughout the human genome. Thus, it was of interest to determine if Rev could functionally interact with selected RcRE elements that map either to HERV-K proviruses or human gene regions. This interaction would have the potential to alter the expression of both HERV-K mRNAs and cellular mRNAs during HIV-1 infection. RESULTS: In this study we employed a combination of RNAseq, bioinformatics and cell-based functional assays. Potential RcREs were identified through a number of bioinformatic approaches. They were then tested for their ability to promote export and translation of a reporter mRNA with a retained intron in conjunction with Rev or Rec. Some of the selected elements functioned well with either Rev, Rec or both, whereas some showed little or no function. Rev function on individual RcREs varied and was also dependent on the Rev sequence. We also performed RNAseq on total and cytoplasmic RNA isolated from SupT1 cells expressing HIV Rev, with or without Tat, or HERV-K Rec. Proviral mRNA from three HERV-K loci (4p16.1b, 22q11.23 and most significantly 3q12.3) accumulated in the cytoplasm in the presence of Rev or Tat and Rev, but not Rec. Consistent with this, the 3' RcRE from 3q12.3 functioned well with HIV-Rev in our reporter assay. In contrast, this RcRE showed little or no function with Rec. CONCLUSIONS: The HIV Rev protein can functionally interact with many RcREs present in the human genome, depending on the RcRE sequence, as well as the Rev sequence. This leads to export of some of the HERV-K proviral mRNAs and also has the potential to change the expression of non-viral genes.

NF-κB upregulates glutamine-fructose-6-phosphate transaminase 2 to promote migration in non-small cell lung cancer.

BACKGROUND: Epithelial-to-mesenchymal transition (EMT) results in changes that promote de-differentiation, migration, and invasion in non-small cell lung cancer (NSCLC). While it is recognized that EMT promotes altered energy utilization, identification of metabolic pathways that link EMT with cancer progression is needed. Work presented here indicates that mesenchymal NSCLC upregulates glutamine-fructose-6-phosphate transaminase 2 (GFPT2). GFPT2 is the rate-limiting enzyme in the synthesis of uridine diphosphate N-acetylglucosamine (UDP-GlcNAc). UDP-GlcNAc is the obligate activator of O-linked N-acetylglucosamine transferase (OGT). METHODS: Analysis of our transcriptomic data indicates that GFPT2 is one of the most significantly upregulated metabolic genes in mesenchymal NSCLC. Ectopic GFPT2 expression, as well as gene silencing strategies were used to determine the importance of this metabolic enzyme in regulating EMT-driven processes of cell motility and invasion. RESULTS: Our work demonstrates that GFPT2 is transcriptionally upregulated by NF-κB and repressed by the NAD+-dependent deacetylase SIRT6. Depletion of GFPT2 expression in NSCLC highlights its importance in regulating cell migration and invasion during EMT. CONCLUSIONS: Consistent with GFPT2 promoting cancer progression, we find that elevated GFPT2 expression correlates with poor clinical outcome in NSCLC. Modulation of GFPT2 activity offers a potentially important therapeutic target to combat NSCLC disease progression.

An evolutionarily 'young' lysine residue in histone H3 attenuates transcriptional output in Saccharomyces cerevisiae.

The DNA entry and exit points on the nucleosome core regulate the initial invasion of the nucleosome by factors requiring access to the underlying DNA. Here we describe in vivo consequences of eliminating a single protein-DNA interaction at this position through mutagenesis of histone H3 Lys 42 to alanine. This substitution has a dramatic effect on the Saccharomyces cerevisiae transcriptome in both the transcriptional output and landscape of mRNA species produced. We attribute this in part to decreased histone H3 occupancy at transcriptionally active loci, leading to enhanced elongation. Additionally we show that this lysine is methylated in vivo, and genetic studies of methyl-lysine mimics suggest that this modification may be crucial in attenuating gene expression. Interestingly, this site of methylation is unique to Ascomycota, suggesting a recent evolutionary innovation that highlights the evolvability of post-translational modifications of chromatin.

Second-generation method for analysis of chromatin binding with formaldehyde-cross-linking kinetics.

Formaldehyde-cross-linking underpins many of the most commonly used experimental approaches in the chromatin field, especially in capturing site-specific protein-DNA interactions. Extending such assays to assess the stability and binding kinetics of protein-DNA interactions is more challenging, requiring absolute measurements with a relatively high degree of physical precision. We previously described an experimental framework called the cross-linking kinetics (CLK) assay, which uses time-dependent formaldehyde-cross-linking data to extract kinetic parameters of chromatin binding. Many aspects of formaldehyde behavior in cells are unknown or undocumented, however, and could potentially affect CLK data analyses. Here, we report biochemical results that better define the properties of formaldehyde-cross-linking in budding yeast cells. These results have the potential to inform interpretations of "standard" chromatin assays, including chromatin immunoprecipitation. Moreover, the chemical complexity we uncovered resulted in the development of an improved method for measuring binding kinetics with the CLK approach. Optimum conditions included an increased formaldehyde concentration and more robust glycine-quench conditions. Notably, we observed that formaldehyde-cross-linking rates can vary dramatically for different protein-DNA interactions in vivo Some interactions were cross-linked much faster than the in vivo macromolecular interactions, making them suitable for kinetic analysis. For other interactions, we found the cross-linking reaction occurred on the same time scale or slower than binding dynamics; for these interactions, it was sometimes possible to compute the in vivo equilibrium-binding constant but not binding on- and off-rates. This improved method yields more accurate in vivo binding kinetics estimates on the minute time scale.

The Modifier of Transcription 1 (Mot1) ATPase and Spt16 Histone Chaperone Co-regulate Transcription through Preinitiation Complex Assembly and Nucleosome Organization.

Modifier of transcription 1 (Mot1) is a conserved and essential Swi2/Snf2 ATPase that can remove TATA-binding protein (TBP) from DNA using ATP hydrolysis and in so doing exerts global effects on transcription. Spt16 is also essential and functions globally in transcriptional regulation as a component of the facilitates chromatin transcription (FACT) histone chaperone complex. Here we demonstrate that Mot1 and Spt16 regulate a largely overlapping set of genes in Saccharomyces cerevisiae. As expected, Mot1 was found to control TBP levels at co-regulated promoters. In contrast, Spt16 did not affect TBP recruitment. On a global scale, Spt16 was required for Mot1 promoter localization, and Mot1 also affected Spt16 localization to genes. Interestingly, we found that Mot1 has an unanticipated role in establishing or maintaining the occupancy and positioning of nucleosomes at the 5' ends of genes. Spt16 has a broad role in regulating chromatin organization in gene bodies, including those nucleosomes affected by Mot1. These results suggest that the large scale overlap in Mot1 and Spt16 function arises from a combination of both their unique and shared functions in transcription complex assembly and chromatin structure regulation.