p53 Activates the Long Noncoding RNA Pvt1b to Inhibit Myc and Suppress Tumorigenesis.

The tumor suppressor p53 transcriptionally activates target genes to suppress cellular proliferation during stress. p53 has also been implicated in the repression of the proto-oncogene Myc, but the mechanism has remained unclear. Here, we identify Pvt1b, a p53-dependent isoform of the long noncoding RNA (lncRNA) Pvt1, expressed 50 kb downstream of Myc, which becomes induced by DNA damage or oncogenic signaling and accumulates near its site of transcription. We show that production of the Pvt1b RNA is necessary and sufficient to suppress Myc transcription in cis without altering the chromatin organization of the locus. Inhibition of Pvt1b increases Myc levels and transcriptional activity and promotes cellular proliferation. Furthermore, Pvt1b loss accelerates tumor growth, but not tumor progression, in an autochthonous mouse model of lung cancer. These findings demonstrate that Pvt1b acts at the intersection of the p53 and Myc transcriptional networks to reinforce the anti-proliferative activities of p53.

TimeLapse-seq: adding a temporal dimension to RNA sequencing through nucleoside recoding.

RNA sequencing (RNA-seq) offers a snapshot of cellular RNA populations, but not temporal information about the sequenced RNA. Here we report TimeLapse-seq, which uses oxidative-nucleophilic-aromatic substitution to convert 4-thiouridine into cytidine analogs, yielding apparent U-to-C mutations that mark new transcripts upon sequencing. TimeLapse-seq is a single-molecule approach that is adaptable to many applications and reveals RNA dynamics and induced differential expression concealed in traditional RNA-seq.

Global Profiling of Cellular Substrates of Human Dcp2.

Decapping is the first committed step in 5'-to-3' RNA decay, and in the cytoplasm of human cells, multiple decapping enzymes regulate the stabilities of distinct subsets of cellular transcripts. However, the complete set of RNAs regulated by any individual decapping enzyme remains incompletely mapped, and no consensus sequence or property is currently known to unambiguously predict decapping enzyme substrates. Dcp2 was the first-identified and best-studied eukaryotic decapping enzyme, but it has been shown to regulate the stability of <400 transcripts in mammalian cells to date. Here, we globally profile changes in the stability of the human transcriptome in Dcp2 knockout cells via TimeLapse-seq. We find that P-body enrichment is the strongest correlate of Dcp2-dependent decay and that modification with m6A exhibits an additive effect with P-body enrichment for Dcp2 targeting. These results are consistent with a model in which P-bodies represent sites where translationally repressed transcripts are sorted for decay by soluble cytoplasmic decay complexes through additional molecular marks.

The NBDY Microprotein Regulates Cellular RNA Decapping.

Proteogenomic identification of translated small open reading frames in humans has revealed thousands of microproteins, or polypeptides of fewer than 100 amino acids, that were previously invisible to geneticists. Hundreds of microproteins have been shown to be essential for cell growth and proliferation, and many regulate macromolecular complexes. One such regulatory microprotein is NBDY, a 68-amino acid component of the human cytoplasmic RNA decapping complex. Heterologously expressed NBDY was previously reported to regulate cytoplasmic ribonucleoprotein granules known as P-bodies and reporter gene stability, but the global effect of endogenous NBDY on the cellular transcriptome remained undefined. In this work, we demonstrate that endogenous NBDY directly interacts with the human RNA decapping complex through EDC4 and DCP1A and localizes to P-bodies. Global profiling of RNA stability changes in NBDY knockout (KO) cells reveals dysregulated stability of more than 1400 transcripts. DCP2 substrate transcript half-lives are both increased and decreased in NBDY KO cells, which correlates with 5' UTR length. NBDY deletion additionally alters the stability of non-DCP2 target transcripts, possibly as a result of downregulated expression of nonsense-mediated decay factors in NBDY KO cells. We present a comprehensive model of the regulation of RNA stability by NBDY.

Expanding the Nucleoside Recoding Toolkit: Revealing RNA Population Dynamics with 6-Thioguanosine.

RNA-sequencing (RNA-seq) measures RNA abundance in a biological sample but does not provide temporal information about the sequenced RNAs. Metabolic labeling can be used to distinguish newly made RNAs from pre-existing RNAs. Mutations induced from chemical recoding of the hydrogen bonding pattern of the metabolic label can reveal which RNAs are new in the context of a sequencing experiment. These nucleotide recoding strategies have been developed for a single uridine analogue, 4-thiouridine (s4U), limiting the scope of these experiments. Here we report the first use of nucleoside recoding with a guanosine analogue, 6-thioguanosine (s6G). Using TimeLapse sequencing (TimeLapse-seq), s6G can be recoded under RNA-friendly oxidative nucleophilic-aromatic substitution conditions to produce adenine analogues (substituted 2-aminoadenosines). We demonstrate the first use of s6G recoding experiments to reveal transcriptome-wide RNA population dynamics.

Structural and spectroscopic characterization of iron(II), cobalt(II), and nickel(II) ortho-dihalophenolate complexes: insights into metal-halogen secondary bonding.

Metal complexes incorporating the tris(3,5-diphenylpyrazolyl)borate ligand (Tp(Ph2)) and ortho-dihalophenolates were synthesized and characterized in order to explore metal-halogen secondary bonding in biorelevant model complexes. The complexes Tp(Ph2)ML were synthesized and structurally characterized, where M was Fe(II), Co(II), or Ni(II) and L was either 2,6-dichloro- or 2,6-dibromophenolate. All six complexes exhibited metal-halogen secondary bonds in the solid state, with distances ranging from 2.56 Å for the Tp(Ph2)Ni(2,6-dichlorophenolate) complex to 2.88 Å for the Tp(Ph2)Fe(2,6-dibromophenolate) complex. Variable temperature NMR spectra of the Tp(Ph2)Co(2,6-dichlorophenolate) and Tp(Ph2)Ni(2,6-dichlorophenolate) complexes showed that rotation of the phenolate, which requires loss of the secondary bond, has an activation barrier of ~30 and ~37 kJ/mol, respectively. Density functional theory calculations support the presence of a barrier for disruption of the metal-halogen interaction during rotation of the phenolate. On the other hand, calculations using the spectroscopically calibrated angular overlap method suggest essentially no contribution of the halogen to the ligand-field splitting. Overall, these results provide the first quantitative measure of the strength of a metal-halogen secondary bond and demonstrate that it is a weak noncovalent interaction comparable in strength to a hydrogen bond. These results provide insight into the origin of the specificity of the enzyme 2,6-dichlorohydroquinone 1,2-dioxygenase (PcpA), which is specific for ortho-dihalohydroquinone substrates and phenol inhibitors.

Broad compatibility between yeast UAS elements and core promoters and identification of promoter elements that determine cofactor specificity.

Three classes of yeast protein-coding genes are distinguished by their dependence on the transcription cofactors TFIID, SAGA, and Mediator (MED) Tail, but whether this dependence is determined by the core promoter, upstream activating sequences (UASs), or other gene features is unclear. Also unclear is whether UASs can broadly activate transcription from the different promoter classes. Here, we measure transcription and cofactor specificity for thousands of UAS-core promoter combinations and find that most UASs broadly activate promoters regardless of regulatory class, while few display strong promoter specificity. However, matching UASs and promoters from the same gene class is generally important for optimal expression. We find that sensitivity to rapid depletion of MED Tail or SAGA is dependent on the identity of both UAS and core promoter, while dependence on TFIID localizes to only the promoter. Finally, our results suggest the role of TATA and TATA-like promoter sequences in MED Tail function.

Improving the study of RNA dynamics through advances in RNA-seq with metabolic labeling and nucleotide-recoding chemistry.

RNA metabolic labeling using 4-thiouridine (s4U) captures the dynamics of RNA synthesis and decay. The power of this approach is dependent on appropriate quantification of labeled and unlabeled sequencing reads, which can be compromised by the apparent loss of s4U-labeled reads in a process we refer to as dropout. Here we show that s4U-containing transcripts can be selectively lost when RNA samples are handled under sub-optimal conditions, but that this loss can be minimized using an optimized protocol. We demonstrate a second cause of dropout in nucleotide recoding and RNA sequencing (NR-seq) experiments that is computational and downstream of library preparation. NR-seq experiments involve chemically converting s4U from a uridine analog to a cytidine analog and using the apparent T-to-C mutations to identify the populations of newly synthesized RNA. We show that high levels of T-to-C mutations can prevent read alignment with some computational pipelines, but that this bias can be overcome using improved alignment pipelines. Importantly, kinetic parameter estimates are affected by dropout independent of the NR chemistry employed, and all chemistries are practically indistinguishable in bulk, short-read RNA-seq experiments. Dropout is an avoidable problem that can be identified by including unlabeled controls, and mitigated through improved sample handing and read alignment that together improve the robustness and reproducibility of NR-seq experiments.

Discovery of cellular substrates of human RNA-decapping enzyme DCP2 using a stapled bicyclic peptide inhibitor.

DCP2 is an RNA-decapping enzyme that controls the stability of human RNAs that encode factors functioning in transcription and the immune response. While >1,800 human DCP2 substrates have been identified, compensatory expression changes secondary to genetic ablation of DCP2 have complicated a complete mapping of its regulome. Cell-permeable, selective chemical inhibitors of DCP2 could provide a powerful tool to study DCP2 specificity. Here, we report phage display selection of CP21, a bicyclic peptide ligand to DCP2. CP21 has high affinity and selectivity for DCP2 and inhibits DCP2 decapping activity toward selected RNA substrates in human cells. CP21 increases formation of P-bodies, liquid condensates enriched in intermediates of RNA decay, in a manner that resembles the deletion or mutation of DCP2. We used CP21 to identify 76 previously unreported DCP2 substrates. This work demonstrates that DCP2 inhibition can complement genetic approaches to study RNA decay.

Gaining insight into transcriptome-wide RNA population dynamics through the chemistry of 4-thiouridine.

Cellular RNA levels are the result of a juggling act between RNA transcription, processing, and degradation. By tuning one or more of these parameters, cells can rapidly alter the available pool of transcripts in response to stimuli. While RNA sequencing (RNA-seq) is a vital method to quantify RNA levels genome-wide, it is unable to capture the dynamics of different RNA populations at steady-state or distinguish between different mechanisms that induce changes to the steady-state (i.e., altered rate of transcription vs. degradation). The dynamics of different RNA populations can be studied by targeted incorporation of noncanonical nucleosides. 4-Thiouridine (s4 U) is a commonly used and versatile RNA metabolic label that allows the study of many properties of RNA metabolism from synthesis to degradation. Numerous experimental strategies have been developed that leverage the power of s4 U to label newly transcribed RNA in whole cells, followed by enrichment with activated disulfides or chemistry to induce C mutations at sites of s4 U during sequencing. This review presents existing methods to study RNA population dynamics genome-wide using s4 U metabolic labeling, as well as a discussion of considerations and challenges when designing s4 U metabolic labeling experiments. This article is categorized under: RNA Methods > RNA Analyses in Cells RNA Turnover and Surveillance > Regulation of RNA Stability.