Publications by authors named "Kevin Struhl"

126 Publications

S100A8/S100A9 cytokine acts as a transcriptional coactivator during breast cellular transformation.

Sci Adv 2021 Jan 1;7(1). Epub 2021 Jan 1.

Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School Boston, MA 02115, USA.

Cytokines are extracellular proteins that convey messages between cells by interacting with cognate receptors at the cell surface and triggering signaling pathways that alter gene expression and other phenotypes in an autocrine or paracrine manner. Here, we show that the calcium-dependent cytokines S100A8 and S100A9 are recruited to numerous promoters and enhancers in a model of breast cellular transformation. This recruitment is associated with multiple DNA sequence motifs recognized by DNA binding transcription factors that are linked to transcriptional activation and are important for transformation. The cytokines interact with these transcription factors in nuclear extracts, and they activate transcription when artificially recruited to a target promoter. Nuclear-specific expression of S100A8/A9 promotes oncogenic transcription and leads to enhanced breast transformation phenotype. These results suggest that, in addition to its classical cytokine function, S100A8/A9 can act as a transcriptional coactivator.
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http://dx.doi.org/10.1126/sciadv.abe5357DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7775746PMC
January 2021

Pheno-RNA, a method to associate genes with a specific phenotype, identifies genes linked to cellular transformation.

Proc Natl Acad Sci U S A 2020 11 3;117(46):28925-28929. Epub 2020 Nov 3.

Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, Boston, MA 02115

Cellular transformation is associated with dramatic changes in gene expression, but it is difficult to determine which regulated genes are oncogenically relevant. Here we describe Pheno-RNA, a general approach to identifying candidate genes associated with a specific phenotype. Specifically, we generate a "phenotypic series" by treating a nontransformed breast cell line with a wide variety of molecules that induce cellular transformation to various extents. By performing transcriptional profiling across this phenotypic series, the expression profile of every gene can be correlated with the strength of the transformed phenotype. We identify ∼200 genes whose expression profiles are very highly correlated with the transformation phenotype, strongly suggesting their importance in transformation. Within biological categories linked to cancer, some genes show high correlations with the transformed phenotype, but others do not. Many genes whose expression profiles are highly correlated with transformation have never been associated with cancer, suggesting the involvement of heretofore unknown genes in cancer.
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http://dx.doi.org/10.1073/pnas.2014165117DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7682411PMC
November 2020

The transcriptional elongation rate regulates alternative polyadenylation in yeast.

Elife 2020 08 26;9. Epub 2020 Aug 26.

Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, Boston, United States.

Yeast cells undergoing the diauxic response show a striking upstream shift in poly(A) site utilization, with increased use of ORF-proximal poly(A) sites resulting in shorter 3' mRNA isoforms for most genes. This altered poly(A) pattern is extremely similar to that observed in cells containing Pol II derivatives with slow elongation rates. Conversely, cells containing derivatives with fast elongation rates show a subtle downstream shift in poly(A) sites. Polyadenylation patterns of many genes are sensitive to both fast and slow elongation rates, and a global shift of poly(A) utilization is strongly linked to increased purine content of sequences flanking poly(A) sites. Pol II processivity is impaired in diauxic cells, but strains with reduced processivity and normal Pol II elongation rates have normal polyadenylation profiles. Thus, Pol II elongation speed is important for poly(A) site selection and for regulating poly(A) patterns in response to environmental conditions.
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http://dx.doi.org/10.7554/eLife.59810DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7532003PMC
August 2020

Promoter-specific dynamics of TATA-binding protein association with the human genome.

Genome Res 2019 12 15;29(12):1939-1950. Epub 2019 Nov 15.

Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, Boston, Massachusetts 02115, USA.

Transcription factor binding to target sites in vivo is a dynamic process that involves cycles of association and dissociation, with individual proteins differing in their binding dynamics. The dynamics at individual sites on a genomic scale have been investigated in yeast cells, but comparable experiments have not been done in multicellular eukaryotes. Here, we describe a tamoxifen-inducible, time-course ChIP-seq approach to measure transcription factor binding dynamics at target sites throughout the human genome. As observed in yeast cells, the TATA-binding protein (TBP) typically displays rapid turnover at RNA polymerase (Pol) II-transcribed promoters, slow turnover at Pol III promoters, and very slow turnover at the Pol I promoter. Turnover rates vary widely among Pol II promoters in a manner that does not correlate with the level of TBP occupancy. Human Pol II promoters with slow TBP dissociation preferentially contain a TATA consensus motif, support high transcriptional activity of downstream genes, and are linked with specific activators and chromatin remodelers. These properties of human promoters with slow TBP turnover differ from those of yeast promoters with slow turnover. These observations suggest that TBP binding dynamics differentially affect promoter function and gene expression, possibly at the level of transcriptional reinitiation/bursting.
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http://dx.doi.org/10.1101/gr.254466.119DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6886507PMC
December 2019

Inflammatory regulatory network mediated by the joint action of NF-kB, STAT3, and AP-1 factors is involved in many human cancers.

Proc Natl Acad Sci U S A 2019 05 25;116(19):9453-9462. Epub 2019 Mar 25.

Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, Boston, MA 02115;

Using an inducible, inflammatory model of breast cellular transformation, we describe the transcriptional regulatory network mediated by STAT3, NF-κB, and AP-1 factors on a genomic scale. These proinflammatory regulators form transcriptional complexes that directly regulate the expression of hundreds of genes in oncogenic pathways via a positive feedback loop. This transcriptional feedback loop and associated network functions to various extents in many types of cancer cells and patient tumors, and it is the basis for a cancer inflammation index that defines cancer types by functional criteria. We identify a network of noninflammatory genes whose expression is well correlated with the cancer inflammatory index. Conversely, the cancer inflammation index is negatively correlated with the expression of genes involved in DNA metabolism, and transformation is associated with genome instability. We identify drugs whose efficacy in cell lines is correlated with the cancer inflammation index, suggesting the possibility of using this index for personalized cancer therapy. Inflammatory tumors are preferentially associated with infiltrating immune cells that might be recruited to the site of the tumor via inflammatory molecules produced by the cancer cells.
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http://dx.doi.org/10.1073/pnas.1821068116DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6511065PMC
May 2019

Requirements for RNA polymerase II preinitiation complex formation in vivo.

Elife 2019 01 25;8. Epub 2019 Jan 25.

Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, Boston, United States.

Transcription by RNA polymerase II requires assembly of a preinitiation complex (PIC) composed of general transcription factors (GTFs) bound at the promoter. In vitro, some GTFs are essential for transcription, whereas others are not required under certain conditions. PICs are stable in the absence of nucleotide triphosphates, and subsets of GTFs can form partial PICs. By depleting individual GTFs in yeast cells, we show that all GTFs are essential for TBP binding and transcription, suggesting that partial PICs do not exist at appreciable levels in vivo. Depletion of FACT, a histone chaperone that travels with elongating Pol II, strongly reduces PIC formation and transcription. In contrast, TBP-associated factors (TAFs) contribute to transcription of most genes, but TAF-independent transcription occurs at substantial levels, preferentially at promoters containing TATA elements. PICs are absent in cells deprived of uracil, and presumably UTP, suggesting that transcriptionally inactive PICs are removed from promoters in vivo.
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http://dx.doi.org/10.7554/eLife.43654DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6366898PMC
January 2019

Lysine methyltransferase 2D regulates pancreatic carcinogenesis through metabolic reprogramming.

Gut 2019 07 18;68(7):1271-1286. Epub 2018 Oct 18.

Center for Systems Biomedicine, Vatche and Tamar Manoukian Division of Digestive Diseases, David Geffen School of Medicine, University of California at Los Angeles, Los Angeles, California, USA.

Objective: Despite advances in the identification of epigenetic alterations in pancreatic cancer, their biological roles in the pathobiology of this dismal neoplasm remain elusive. Here, we aimed to characterise the functional significance of histone lysine methyltransferases (KMTs) and demethylases (KDMs) in pancreatic tumourigenesis.

Design: DNA methylation sequencing and gene expression microarrays were employed to investigate CpG methylation and expression patterns of KMTs and KDMs in pancreatic cancer tissues versus normal tissues. Gene expression was assessed in five cohorts of patients by reverse transcription quantitative-PCR. Molecular analysis and functional assays were conducted in genetically modified cell lines. Cellular metabolic rates were measured using an XF24-3 Analyzer, while quantitative evaluation of lipids was performed by liquid chromatography-mass spectrometry (LC-MS) analysis. Subcutaneous xenograft mouse models were used to evaluate pancreatic tumour growth in vivo.

Results: We define a new antitumorous function of the histone lysine (K)-specific methyltransferase 2D (KMT2D) in pancreatic cancer. is transcriptionally repressed in human pancreatic tumours through DNA methylation. Clinically, lower levels of this methyltransferase associate with poor prognosis and significant weight alterations. RNAi-based genetic inactivation of KMT2D promotes tumour growth and results in loss of H3K4me3 mark. In addition, KMT2D inhibition increases aerobic glycolysis and alters the lipidomic profiles of pancreatic cancer cells. Further analysis of this phenomenon identified the glucose transporter SLC2A3 as a mediator of KMT2D-induced changes in cellular, metabolic and proliferative rates.

Conclusion: Together our findings define a new tumour suppressor function of KMT2D through the regulation of glucose/fatty acid metabolism in pancreatic cancer.
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http://dx.doi.org/10.1136/gutjnl-2017-315690DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6697184PMC
July 2019

Extensive Structural Differences of Closely Related 3' mRNA Isoforms: Links to Pab1 Binding and mRNA Stability.

Mol Cell 2018 12 11;72(5):849-861.e6. Epub 2018 Oct 11.

Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, Boston, MA 02115, USA. Electronic address:

Alternative polyadenylation generates numerous 3' mRNA isoforms that can vary in biological properties, such as stability and localization. We developed methods to obtain transcriptome-scale structural information and protein binding on individual 3' mRNA isoforms in vivo. Strikingly, near-identical mRNA isoforms can possess dramatically different structures throughout the 3' UTR. Analyses of identical mRNAs in different species or refolded in vitro indicate that structural differences in vivo are often due to trans-acting factors. The level of Pab1 binding to poly(A)-containing isoforms is surprisingly variable, and differences in Pab1 binding correlate with the extent of structural variation for closely spaced isoforms. A pattern encompassing single-strandedness near the 3' terminus, double-strandedness of the poly(A) tail, and low Pab1 binding is associated with mRNA stability. Thus, individual 3' mRNA isoforms can be remarkably different physical entities in vivo. Sequences responsible for isoform-specific structures, differential Pab1 binding, and mRNA stability are evolutionarily conserved, indicating biological function.
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http://dx.doi.org/10.1016/j.molcel.2018.08.044DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6289678PMC
December 2018

Targeted profiling of RNA translation reveals mTOR-4EBP1/2-independent translation regulation of mRNAs encoding ribosomal proteins.

Proc Natl Acad Sci U S A 2018 10 17;115(40):E9325-E9332. Epub 2018 Sep 17.

Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, MA 02215;

The PI3K-Akt-mTOR signaling pathway is a master regulator of RNA translation. Pharmacological inhibition of this pathway preferentially and coordinately suppresses, in a 4EBP1/2-dependent manner, translation of mRNAs encoding ribosomal proteins. However, it is unclear whether mechanistic target of rapamycin (mTOR)-4EBP1/2 is the exclusive translation regulator of this group of genes, and furthermore, systematic searches for novel translation modulators have been immensely challenging because of difficulties in scaling existing RNA translation profiling assays. Here, we developed a rapid and highly scalable approach for gene-specific quantitation of RNA translation, termed Targeted Profiling of RNA Translation (TPRT). We applied this technique in a chemical screen for translation modulators, and identified numerous preclinical and clinical therapeutic compounds, with diverse nominal targets, that preferentially suppress translation of ribosomal proteins. Surprisingly, some of these compounds act in a manner that bypasses canonical regulation by mTOR-4EBP1/2. Instead, these compounds exert their translation effects in a manner that is dependent on GCN2-eIF2α, a central signaling axis within the integrated stress response. Furthermore, we were also able to identify metabolic perturbations that also suppress ribosomal protein translation in an mTOR-independent manner. Together, we describe a translation assay that is directly applicable to large-scale RNA translation studies, and that enabled us to identify a noncanonical, mTOR-independent mode for translation regulation of ribosomal proteins.
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http://dx.doi.org/10.1073/pnas.1805782115DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6176620PMC
October 2018

Nutrient Deprivation Elicits a Transcriptional and Translational Inflammatory Response Coupled to Decreased Protein Synthesis.

Cell Rep 2018 08;24(6):1415-1424

Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, Boston, MA 02115, USA. Electronic address:

Nutrient deprivation inhibits mRNA translation through mTOR and eIF2α signaling, but it is unclear how the translational program is controlled to reflect the degree of a metabolic stress. In a model of breast cellular transformation, various forms of nutrient deprivation differentially affect the rate of protein synthesis and its recovery over time. Genome-wide translational profiling of glutamine-deprived cells reveals a rapid upregulation of mRNAs containing uORFs and downregulation of ribosomal protein mRNAs, which are followed by selective translation of cytokine and inflammatory mRNAs. Transcription and translation of inflammatory and cytokine genes are stimulated in response to diverse metabolic stresses and depend on eIF2α phosphorylation, with the extent of stimulation correlating with the decrease in global protein synthesis. In accord with the inflammatory stimulus, glutamine deprivation stimulates the migration of transformed cells. Thus, pro-inflammatory gene expression is coupled to metabolic stress, and this can affect cancer cell behavior upon nutrient limitation.
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http://dx.doi.org/10.1016/j.celrep.2018.07.021DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6419098PMC
August 2018

Genome-scale identification of transcription factors that mediate an inflammatory network during breast cellular transformation.

Nat Commun 2018 05 25;9(1):2068. Epub 2018 May 25.

Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, Boston, MA, 02115, USA.

Transient activation of Src oncoprotein in non-transformed, breast epithelial cells can initiate an epigenetic switch to the stably transformed state via a positive feedback loop that involves the inflammatory transcription factors STAT3 and NF-κB. Here, we develop an experimental and computational pipeline that includes 1) a Bayesian network model (AccessTF) that accurately predicts protein-bound DNA sequence motifs based on chromatin accessibility, and 2) a scoring system (TFScore) that rank-orders transcription factors as candidates for being important for a biological process. Genetic experiments validate TFScore and suggest that more than 40 transcription factors contribute to the oncogenic state in this model. Interestingly, individual depletion of several of these factors results in similar transcriptional profiles, indicating that a complex and interconnected transcriptional network promotes a stable oncogenic state. The combined experimental and computational pipeline represents a general approach to comprehensively identify transcriptional regulators important for a biological process.
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http://dx.doi.org/10.1038/s41467-018-04406-2DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5970197PMC
May 2018

The Ground State and Evolution of Promoter Region Directionality.

Cell 2017 Aug 10;170(5):889-898.e10. Epub 2017 Aug 10.

Department of Genetics, Harvard Medical School, Boston, MA 02115, USA. Electronic address:

Eukaryotic promoter regions are frequently divergently transcribed in vivo, but it is unknown whether the resultant antisense RNAs are a mechanistic by-product of RNA polymerase II (Pol II) transcription or biologically meaningful. Here, we use a functional evolutionary approach that involves nascent transcript mapping in S. cerevisiae strains containing foreign yeast DNA. Promoter regions in foreign environments lose the directionality they have in their native species. Strikingly, fortuitous promoter regions arising in foreign DNA produce equal transcription in both directions, indicating that divergent transcription is a mechanistic feature that does not imply a function for these transcripts. Fortuitous promoter regions arising during evolution promote bidirectional transcription and over time are purged through mutation or retained to enable new functionality. Similarly, human transcription is more bidirectional at newly evolved enhancers and promoter regions. Thus, promoter regions are intrinsically bidirectional and are shaped by evolution to bias transcription toward coding versus non-coding RNAs.
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http://dx.doi.org/10.1016/j.cell.2017.07.006DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5576552PMC
August 2017

Evidence that Mediator is essential for Pol II transcription, but is not a required component of the preinitiation complex in vivo.

Elife 2017 07 12;6. Epub 2017 Jul 12.

Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School Boston, Boston, United States.

The Mediator complex has been described as a general transcription factor, but it is unclear if it is essential for Pol II transcription and/or is a required component of the preinitiation complex (PIC) in vivo. Here, we show that depletion of individual subunits, even those essential for cell growth, causes a general but only modest decrease in transcription. In contrast, simultaneous depletion of all Mediator modules causes a drastic decrease in transcription. Depletion of head or middle subunits, but not tail subunits, causes a downstream shift in the Pol II occupancy profile, suggesting that Mediator at the core promoter inhibits promoter escape. Interestingly, a functional PIC and Pol II transcription can occur when Mediator is not detected at core promoters. These results provide strong evidence that Mediator is essential for Pol II transcription and stimulates PIC formation, but it is not a required component of the PIC in vivo.
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http://dx.doi.org/10.7554/eLife.28447DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5529107PMC
July 2017

Mediator Undergoes a Compositional Change during Transcriptional Activation.

Mol Cell 2016 11 20;64(3):443-454. Epub 2016 Oct 20.

Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, Boston, MA 02115, USA. Electronic address:

Mediator is a transcriptional co-activator recruited to enhancers by DNA-binding activators, and it also interacts with RNA polymerase (Pol) II as part of the preinitiation complex (PIC). We demonstrate that a single Mediator complex associates with the enhancer and core promoter in vivo, indicating that it can physically bridge these transcriptional elements. However, the Mediator kinase module associates strongly with the enhancer, but not with the core promoter, and it dissociates from the enhancer upon depletion of the TFIIH kinase. Severing the kinase module from Mediator by removing the connecting subunit Med13 does not affect Mediator association at the core promoter but increases occupancy at enhancers. Thus, Mediator undergoes a compositional change in which the kinase module, recruited via Mediator to the enhancer, dissociates from Mediator to permit association with Pol II and the PIC. As such, Mediator acts as a dynamic bridge between the enhancer and core promoter.
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http://dx.doi.org/10.1016/j.molcel.2016.09.015DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5096951PMC
November 2016

LINC00520 is induced by Src, STAT3, and PI3K and plays a functional role in breast cancer.

Oncotarget 2016 Dec;7(50):81981-81994

Department of Pathology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA.

Long non-coding RNAs (lncRNAs) have been implicated in normal cellular homeostasis as well as pathophysiological conditions, including cancer. Here we performed global gene expression profiling of mammary epithelial cells transformed by oncogenic v-Src, and identified a large subset of uncharacterized lncRNAs potentially involved in breast cancer development. Specifically, our analysis revealed a novel lncRNA, LINC00520 that is upregulated upon ectopic expression of oncogenic v-Src, in a manner that is dependent on the transcription factor STAT3. Similarly, LINC00520 is also increased in mammary epithelial cells transformed by oncogenic PI3K and its expression is decreased upon knockdown of mutant PIK3CA. Additional expression profiling highlight that LINC00520 is elevated in a subset of human breast carcinomas, with preferential enrichment in the basal-like molecular subtype. ShRNA-mediated depletion of LINC00520 results in decreased cell migration and loss of invasive structures in 3D. RNA sequencing analysis uncovers several genes that are differentially expressed upon ectopic expression of LINC00520, a significant subset of which are also induced in v-Src-transformed MCF10A cells. Together, these findings characterize LINC00520 as a lncRNA that is regulated by oncogenic Src, PIK3CA and STAT3, and which may contribute to the molecular etiology of breast cancer.
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http://dx.doi.org/10.18632/oncotarget.11962DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5347668PMC
December 2016

Selectivity of ORC binding sites and the relation to replication timing, fragile sites, and deletions in cancers.

Proc Natl Acad Sci U S A 2016 08 19;113(33):E4810-9. Epub 2016 Jul 19.

Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, Boston, MA 02115;

The origin recognition complex (ORC) binds sites from which DNA replication is initiated. We address ORC binding selectivity in vivo by mapping ∼52,000 ORC2 binding sites throughout the human genome. The ORC binding profile is broader than those of sequence-specific transcription factors, suggesting that ORC is not bound or recruited to specific DNA sequences. Instead, ORC binds nonspecifically to open (DNase I-hypersensitive) regions containing active chromatin marks such as H3 acetylation and H3K4 methylation. ORC sites in early and late replicating regions have similar properties, but there are far more ORC sites in early replicating regions. This suggests that replication timing is due primarily to ORC density and stochastic firing of origins. Computational simulation of stochastic firing from identified ORC sites is in accord with replication timing data. Large genomic regions with a paucity of ORC sites are strongly associated with common fragile sites and recurrent deletions in cancers. We suggest that replication origins, replication timing, and replication-dependent chromosome breaks are determined primarily by the genomic distribution of activator proteins at enhancers and promoters. These activators recruit nucleosome-modifying complexes to create the appropriate chromatin structure that allows ORC binding and subsequent origin firing.
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http://dx.doi.org/10.1073/pnas.1609060113DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4995967PMC
August 2016

Transcriptome-scale RNase-footprinting of RNA-protein complexes.

Nat Biotechnol 2016 Apr 22;34(4):410-3. Epub 2016 Feb 22.

Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, Boston, Massachusetts, USA.

Ribosome profiling is widely used to study translation in vivo, but not all sequence reads correspond to ribosome-protected RNA. Here we describe Rfoot, a computational pipeline that analyzes ribosomal profiling data and identifies native, nonribosomal RNA-protein complexes. We use Rfoot to precisely map RNase-protected regions within small nucleolar RNAs, spliceosomal RNAs, microRNAs, tRNAs, long noncoding (lnc)RNAs and 3' untranslated regions of mRNAs in human cells. We show that RNAs of the same class can show differential complex association. Although only a subset of lncRNAs show RNase footprints, many of these have multiple footprints, and the protected regions are evolutionarily conserved, suggestive of biological functions.
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http://dx.doi.org/10.1038/nbt.3441DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4824641PMC
April 2016

Many lncRNAs, 5'UTRs, and pseudogenes are translated and some are likely to express functional proteins.

Elife 2015 Dec 19;4:e08890. Epub 2015 Dec 19.

Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, Boston, United States.

Using a new bioinformatic method to analyze ribosome profiling data, we show that 40% of lncRNAs and pseudogene RNAs expressed in human cells are translated. In addition, ~35% of mRNA coding genes are translated upstream of the primary protein-coding region (uORFs) and 4% are translated downstream (dORFs). Translated lncRNAs preferentially localize in the cytoplasm, whereas untranslated lncRNAs preferentially localize in the nucleus. The translation efficiency of cytoplasmic lncRNAs is nearly comparable to that of mRNAs, suggesting that cytoplasmic lncRNAs are engaged by the ribosome and translated. While most peptides generated from lncRNAs may be highly unstable byproducts without function, ~9% of the peptides are conserved in ORFs in mouse transcripts, as are 74% of pseudogene peptides, 24% of uORF peptides and 32% of dORF peptides. Analyses of synonymous and nonsynonymous substitution rates of these conserved peptides show that some are under stabilizing selection, suggesting potential functional importance.
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http://dx.doi.org/10.7554/eLife.08890DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4739776PMC
December 2015

Alternative to the soft-agar assay that permits high-throughput drug and genetic screens for cellular transformation.

Proc Natl Acad Sci U S A 2015 May 20;112(18):5708-13. Epub 2015 Apr 20.

Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, Boston, MA 02115;

Colony formation in soft agar is the gold-standard assay for cellular transformation in vitro, but it is unsuited for high-throughput screening. Here, we describe an assay for cellular transformation that involves growth in low attachment (GILA) conditions and is strongly correlated with the soft-agar assay. Using GILA, we describe high-throughput screens for drugs and genes that selectively inhibit or increase transformation, but not proliferation. Such molecules are unlikely to be found through conventional drug screening, and they include kinase inhibitors and drugs for noncancer diseases. In addition to known oncogenes, the genetic screen identifies genes that contribute to cellular transformation. Lastly, we demonstrate the ability of Food and Drug Administration-approved noncancer drugs to selectively kill ovarian cancer cells derived from patients with chemotherapy-resistant disease, suggesting this approach may provide useful information for personalized cancer treatment.
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http://dx.doi.org/10.1073/pnas.1505979112DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4426412PMC
May 2015

Mapping 3' mRNA isoforms on a genomic scale.

Curr Protoc Mol Biol 2015 Apr 1;110:4.23.1-4.23.17. Epub 2015 Apr 1.

Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, Boston, Massachusetts.

Most eukaryotic genes are transcribed into mRNAs with alternative poly(A) sites. Emerging evidence suggests that mRNA isoforms with alternative poly(A) sites can perform critical regulatory functions in numerous biological processes. In recent years, a number of strategies utilizing high-throughput sequencing technologies have been developed to aid in the identification of genome-wide poly(A) sites. This unit describes a modified protocol for a recently published 3'READS (3' region extraction and deep sequencing) method that accurately identifies genome-wide poly(A) sites and that can be used to quantify the relative abundance of the resulting 3' mRNA isoforms. This approach minimizes nonspecific sequence reads due to internal priming and typically yields a high percentage of sequence reads that are ideally suited for accurate poly(A) identification.
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http://dx.doi.org/10.1002/0471142727.mb0423s110DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4397975PMC
April 2015

STAT3 acts through pre-existing nucleosome-depleted regions bound by FOS during an epigenetic switch linking inflammation to cancer.

Epigenetics Chromatin 2015 14;8. Epub 2015 Feb 14.

Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, Boston, MA 02115 USA.

Background: Transient induction of the Src oncoprotein in a non-transformed breast cell line can initiate an epigenetic switch to a cancer cell via a positive feedback loop that involves activation of the signal transducer and activator of transcription 3 protein (STAT3) and NF-κB transcription factors.

Results: We show that during the transformation process, nucleosome-depleted regions (defined by formaldehyde-assisted isolation of regulatory elements (FAIRE)) are largely unchanged and that both before and during transformation, STAT3 binds almost exclusively to previously open chromatin regions. Roughly, a third of the transformation-inducible genes require STAT3 for the induction. STAT3 and NF-κB appear to drive the regulation of different gene sets during the transformation process. Interestingly, STAT3 directly regulates the expression of NFKB1, which encodes a subunit of NF-κB, and IL6, a cytokine that stimulates STAT3 activity. Lastly, many STAT3 binding sites are also bound by FOS and the expression of several AP-1 factors is altered during transformation in a STAT3-dependent manner, suggesting that STAT3 may cooperate with AP-1 proteins.

Conclusions: These observations uncover additional complexities to the inflammatory feedback loop that are likely to contribute to the epigenetic switch. In addition, gene expression changes during transformation, whether driven by pre-existing or induced transcription factors, occur largely through pre-existing nucleosome-depleted regions.
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http://dx.doi.org/10.1186/1756-8935-8-7DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4362815PMC
March 2015

Secondary structures involving the poly(A) tail and other 3' sequences are major determinants of mRNA isoform stability in yeast.

Microb Cell 2014 Apr;1(4):137-139

Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, Boston, MA 02115.

In , previous measurements of mRNA stabilities have been determined on a per-gene basis. We and others have recently shown that yeast genes give rise to a highly heterogeneous population of mRNAs thanks to extensive alternative 3' end formation. Typical genes can have fifty or more distinct mRNA isoforms with 3' endpoints differing by as little as one and as many as hundreds of nucleotides. In our recent paper [Geisberg Cell (2014) 156: 812-824] we measured half-lives of individual mRNA isoforms in by using the anchor away method for the rapid removal of Rpb1, the largest subunit of RNA Polymerase II, from the nucleus, followed by direct RNA sequencing of the cellular mRNA population over time. Combining these two methods allowed us to determine half-lives for more than 20,000 individual mRNA isoforms originating from nearly 5000 yeast genes. We discovered that different 3' mRNA isoforms arising from the same gene can have widely different stabilities, and that such half-life variability across mRNA isoforms from a single gene is highly prevalent in yeast cells. Determining half-lives for many different mRNA isoforms from the same genes allowed us to identify hundreds of RNA sequence elements involved in the stabilization and destabilization of individual isoforms. In many cases, the poly(A) tail is likely to participate in the formation of stability-enhancing secondary structures at mRNA 3' ends. Our results point to an important role for mRNA structure at 3' termini in governing transcript stability, likely by reducing the interaction of the mRNA with the degradation apparatus.
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4178928PMC
http://dx.doi.org/10.15698/mic2014.04.140DOI Listing
April 2014

Metformin and phenformin deplete tricarboxylic acid cycle and glycolytic intermediates during cell transformation and NTPs in cancer stem cells.

Proc Natl Acad Sci U S A 2014 Jul 7;111(29):10574-9. Epub 2014 Jul 7.

Departments of Biological Chemistry and Molecular Pharmacology and

Metformin, a first-line diabetes drug linked to cancer prevention in retrospective clinical analyses, inhibits cellular transformation and selectively kills breast cancer stem cells (CSCs). Although a few metabolic effects of metformin and the related biguanide phenformin have been investigated in established cancer cell lines, the global metabolic impact of biguanides during the process of neoplastic transformation and in CSCs is unknown. Here, we use LC/MS/MS metabolomics (>200 metabolites) to assess metabolic changes induced by metformin and phenformin in an Src-inducible model of cellular transformation and in mammosphere-derived breast CSCs. Although phenformin is the more potent biguanide in both systems, the metabolic profiles of these drugs are remarkably similar, although not identical. During the process of cellular transformation, biguanide treatment prevents the boost in glycolytic intermediates at a specific stage of the pathway and coordinately decreases tricarboxylic acid (TCA) cycle intermediates. In contrast, in breast CSCs, biguanides have a modest effect on glycolytic and TCA cycle intermediates, but they strongly deplete nucleotide triphosphates and may impede nucleotide synthesis. These metabolic profiles are consistent with the idea that biguanides inhibit mitochondrial complex 1, but they indicate that their metabolic effects differ depending on the stage of cellular transformation.
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http://dx.doi.org/10.1073/pnas.1409844111DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4115496PMC
July 2014

TFIIH phosphorylation of the Pol II CTD stimulates mediator dissociation from the preinitiation complex and promoter escape.

Mol Cell 2014 May 17;54(4):601-12. Epub 2014 Apr 17.

Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, Boston, MA 02115, USA. Electronic address:

The transition between transcriptional initiation and elongation by RNA polymerase (Pol) II is associated with phosphorylation of its C-terminal tail (CTD). Depletion of Kin28, the TFIIH subunit that phosphorylates the CTD, does not affect elongation but causes Pol II occupancy profiles to shift upstream in a FACT-independent manner indicative of a defect in promoter escape. Stronger defects in promoter escape are linked to stronger effects on preinitiation complex formation and transcription, suggesting that impairment in promoter escape results in premature dissociation of general factors and Pol II near the promoter. Kin28 has a stronger effect on genes whose transcription is dependent on SAGA as opposed to TFIID. Strikingly, Kin28 depletion causes a dramatic increase in Mediator at the core promoter. These observations suggest that TFIIH phosphorylation of the CTD causes Mediator dissociation, thereby permitting rapid promoter escape of Pol II from the preinitiation complex.
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http://dx.doi.org/10.1016/j.molcel.2014.03.024DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4035452PMC
May 2014

Is DNA methylation of tumour suppressor genes epigenetic?

Authors:
Kevin Struhl

Elife 2014 Mar 12;3:e02475. Epub 2014 Mar 12.

Kevin Struhl is an eLife reviewing editor, and is in the Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, Boston, United States

In colorectal cancer cells, a non-epigenetic transcriptional pathway that is mediated by an oncogene maintains DNA methylation of tumour suppressor genes.
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3949415PMC
http://dx.doi.org/10.7554/eLife.02475DOI Listing
March 2014

Global analysis of mRNA isoform half-lives reveals stabilizing and destabilizing elements in yeast.

Cell 2014 Feb;156(4):812-24

Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, Boston, MA 02115, USA. Electronic address:

We measured half-lives of 21,248 mRNA 3' isoforms in yeast by rapidly depleting RNA polymerase II from the nucleus and performing direct RNA sequencing throughout the decay process. Interestingly, half-lives of mRNA isoforms from the same gene, including nearly identical isoforms, often vary widely. Based on clusters of isoforms with different half-lives, we identify hundreds of sequences conferring stabilization or destabilization upon mRNAs terminating downstream. One class of stabilizing element is a polyU sequence that can interact with poly(A) tails, inhibit the association of poly(A)-binding protein, and confer increased stability upon introduction into ectopic transcripts. More generally, destabilizing and stabilizing elements are linked to the propensity of the poly(A) tail to engage in double-stranded structures. Isoforms engineered to fold into 3' stem-loop structures not involving the poly(A) tail exhibit even longer half-lives. We suggest that double-stranded structures at 3' ends are a major determinant of mRNA stability.
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http://dx.doi.org/10.1016/j.cell.2013.12.026DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3939777PMC
February 2014

Species-specific factors mediate extensive heterogeneity of mRNA 3' ends in yeasts.

Proc Natl Acad Sci U S A 2013 Jul 17;110(27):11073-8. Epub 2013 Jun 17.

Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, Boston, MA 02115, USA.

Most eukaryotic genes express mRNAs with alternative polyadenylation sites at their 3' ends. Here we show that polyadenylated 3' termini in three yeast species (Saccharomyces cerevisiae, Kluyveromyces lactis, and Debaryomyces hansenii) are remarkably heterogeneous. Instead of a few discrete 3' ends, the average yeast gene has an "end zone," a >200 bp window with >60 distinct poly(A) sites, the most used of which represents only 20% of the mRNA molecules. The pattern of polyadenylation within this zone varies across species, with D. hansenii possessing a higher focus on a single dominant point closer to the ORF terminus. Some polyadenylation occurs within mRNA coding regions with a strong bias toward the promoter. The polyadenylation pattern is determined by a highly degenerate sequence over a broad region and by a local sequence that relies on A residues after the cleavage point. Many dominant poly(A) sites are predicted to adopt a common secondary structure that may be recognized by the cleavage/polyadenylation machinery. We suggest that the end zone reflects a region permissive for polyadenylation, within which cleavage occurs preferentially at the A-rich sequence. In S. cerevisiae strains, D. hansenii genes adopt the S. cerevisiae polyadenylation profile, indicating that the polyadenylation pattern is mediated primarily by species-specific factors.
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http://dx.doi.org/10.1073/pnas.1309384110DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3703967PMC
July 2013

NF-Y coassociates with FOS at promoters, enhancers, repetitive elements, and inactive chromatin regions, and is stereo-positioned with growth-controlling transcription factors.

Genome Res 2013 Aug 17;23(8):1195-209. Epub 2013 Apr 17.

Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, Boston, Massachusetts 02115, USA.

NF-Y, a trimeric transcription factor (TF) composed of two histone-like subunits (NF-YB and NF-YC) and a sequence-specific subunit (NF-YA), binds to the CCAAT motif, a common promoter element. Genome-wide mapping reveals 5000-15,000 NF-Y binding sites depending on the cell type, with the NF-YA and NF-YB subunits binding asymmetrically with respect to the CCAAT motif. Despite being characterized as a proximal promoter TF, only 25% of NF-Y sites map to promoters. A comparable number of NF-Y sites are located at enhancers, many of which are tissue specific, and nearly half of the NF-Y sites are in select subclasses of HERV LTR repeats. Unlike most TFs, NF-Y can access its target DNA motif in inactive (nonmodified) or polycomb-repressed chromatin domains. Unexpectedly, NF-Y extensively colocalizes with FOS in all genomic contexts, and this often occurs in the absence of JUN and the AP-1 motif. NF-Y also coassociates with a select cluster of growth-controlling and oncogenic TFs, consistent with the abundance of CCAAT motifs in the promoters of genes overexpressed in cancer. Interestingly, NF-Y and several growth-controlling TFs bind in a stereo-specific manner, suggesting a mechanism for cooperative action at promoters and enhancers. Our results indicate that NF-Y is not merely a commonly used proximal promoter TF, but rather performs a more diverse set of biological functions, many of which are likely to involve coassociation with FOS.
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http://dx.doi.org/10.1101/gr.148080.112DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3730095PMC
August 2013

Determinants of nucleosome positioning.

Nat Struct Mol Biol 2013 Mar;20(3):267-73

Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, Boston, Massachusetts, USA.

Nucleosome positioning is critical for gene expression and most DNA-related processes. Here we review the dominant patterns of nucleosome positioning that have been observed and summarize the current understanding of their underlying determinants. The genome-wide pattern of nucleosome positioning is determined by the combination of DNA sequence, ATP-dependent nucleosome remodeling enzymes and transcription factors that include activators, components of the preinitiation complex and elongating RNA polymerase II. These determinants influence each other such that the resulting nucleosome positioning patterns are likely to differ among genes and among cells in a population, with consequent effects on gene expression.
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http://dx.doi.org/10.1038/nsmb.2506DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3740156PMC
March 2013