Linking uracil base excision repair and 5-fluorouracil toxicity in yeast

5-fluorouracil (5-FU) is a widely used anticancer drug that disrupts pyrimidine nucleotide pool balances and leads to uracil incorporation in DNA, which is then recognized and removed by the uracil base excision repair (BER) pathway. Using complementary biochemical and genetic approaches we have examined the role of uracil BER in the cell killing mechanism of 5-FU. A yeast strain lacking the enzyme uracil DNA glycosylase (Ung1), which excises uracil from the DNA backbone leaving an abasic site, showed significant protection against the toxic effects of 5-FU, a G(1)/S cell cycle arrest phenotype, and accumulated massive amounts of U/A base pairs in its genome (∼4% of T/A pairs were now U/A). A strain lacking the major abasic site endonuclease of Saccharomyces cerevisiae (Apn1) showed significantly increased sensitivity to 5-FU with G(2)/M arrest. Thus, efficient processing of abasic sites by this enzyme is protective against the toxic effects of 5-FU. However, contrary to expectations, the Apn1 deficient strain did not accumulate intact abasic sites, indicating that another repair pathway attempts to process these sites in the absence Apn1, but that this process has catastrophic effects on genome integrity. These findings suggest that new strategies for chemical intervention targeting BER could enhance the effectiveness of this widely used anticancer drug

SAMHD1 is a single-stranded nucleic acid binding protein with no active site-associated nuclease activity.

The HIV-1 restriction factor SAMHD1 is a tetrameric enzyme activated by guanine nucleotides with dNTP triphosphate hydrolase activity (dNTPase). In addition to this established activity, there have been a series of conflicting reports as to whether the enzyme also possesses single-stranded DNA and/or RNA 3\u27-5\u27 exonuclease activity. SAMHD1 was purified using three chromatography steps, over which the DNase activity was largely separated from the dNTPase activity, but the RNase activity persisted. Surprisingly, we found that catalytic and nucleotide activator site mutants of SAMHD1 with no dNTPase activity retained the exonuclease activities. Thus, the exonuclease activity cannot be associated with any known dNTP binding site. Monomeric SAMHD1 was found to bind preferentially to single-stranded RNA, while the tetrameric form required for dNTPase action bound weakly. ssRNA binding, but not ssDNA, induces higher-order oligomeric states that are distinct from the tetrameric form that binds dNTPs. We conclude that the trace exonuclease activities detected in SAMHD1 preparations arise from persistent contaminants that co-purify with SAMHD1 and not from the HD active site. An in vivo model is suggested where SAMHD1 alternates between the mutually exclusive functions of ssRNA binding and dNTP hydrolysis depending on dNTP pool levels and the presence of viral ssRNA

Articles Mechanism of Neomycin and Rev Peptide Binding to the Rev Responsive Element of HIV-1 As Determined by Fluorescence and NMR Spectroscopy †

ABSTRACT: Rev is an essential HIV-1 regulatory protein that binds the Rev responsive element (RRE) within the enV gene of the HIV-1 RNA genome and is involved in transport of unspliced or partially spliced viral mRNA from the cell nucleus to the cytoplasm. Previous studies have shown that a short R-helical peptide derived from Rev , and a truncated form of the RRE sequence provide a useful in vitro system to study this interaction while still preserving the essential aspects of the native complex. We have selectively incorporated the fluorescent probe 2-aminopurine 2′-O-methylriboside (2-AP) into the RRE sequence in nonperturbing positions (A68 and U72) such that the binding of both Rev peptide and aminoglycoside ligands could be characterized directly by fluorescence methods. Rev peptide binding to the RRE-72AP variant resulted in a 2-fold fluorescence increase that provided a useful signal to monitor this binding interaction (K D ) 20 ( 7 nM). Using stopped-flow kinetic measurements, we have shown that specific Rev peptide binding occurs by a two-step process involving diffusion-controlled encounter, followed by isomerization of the RNA. Using the RRE-68AP and -72AP constructs, three classes of binding sites for the aminoglycoside neomycin were unambiguously detected. The first site is noninhibitory to Rev binding (K D ) 0.24 ( 0.040 µM), the second site inhibited Rev binding in a competitive fashion (K D ) 1.8 ( 0.8 µM), and the third much weaker site (or sites) is attributed to nonspecific binding (K D g 40 µM). Complementary NMR measurements have shown that neomycin forms both a specific binary complex with RRE and a specific ternary complex with RRE and Rev. NMR data further suggest that neomycin occupies a similar high-affinity binding site in both the binary and ternary complexes, and that this site is located in the lower stem region of RRE. Rev is an important HIV-1 1 regulatory protein that binds to part of the enV gene within the HIV-1 RNA genome, the so-called Rev responsive element (1-5). Rev is involved in the transport of unspliced and incompletely spliced viral mRNAs, which encode the structural proteins essential for viral replication, from the nucleus to the cytoplasm of the host cell. Stem-loop IIB of RRE, which contains a purinerich internal bulge, has been identified as the high-affinity Rev binding site (6, 7), and small peptides containing a 17 amino acid arginine-rich region of Rev (amino acids 34-51) have been shown to bind this stem-loop specifically (8-14). Since Rev protein binding to viral mRNA at the RRE is essential for HIV replication, acting as a crucial switch between viral latency and active viral replication, the development of new drug therapies against HIV-1 infection based on inhibitors of this essential interaction is desirable. Members of the aminoglycoside family of antibiotics have been shown to interact with a variety of RNA molecules, including the RRE IIB stem-loo

Nontarget DNA binding shapes the dynamic landscape for enzymatic recognition of DNA damage

The DNA repair enzyme human uracil DNA glycosylase (UNG) scans short stretches of genomic DNA and captures rare uracil bases as they transiently emerge from the DNA duplex via spontaneous base pair breathing motions. The process of DNA scanning requires that the enzyme transiently loosen its grip on DNA to allow stochastic movement along the DNA contour, while engaging extrahelical bases requires motions on a more rapid timescale. Here, we use NMR dynamic measurements to show that free UNG has no intrinsic dynamic properties in the millisecond to microsecond and subnanosecond time regimes, and that the act of binding to nontarget DNA reshapes the dynamic landscape to allow productive millisecond motions for scanning and damage recognition. These results suggest that DNA structure and the spontaneous dynamics of base pairs may drive the evolution of a protein sequence that is tuned to respond to this dynamic regime

Mimicking damaged DNA with a small molecule inhibitor of human UNG2

Human nuclear uracil DNA glycosylase (UNG2) is a cellular DNA repair enzyme that is essential for a number of diverse biological phenomena ranging from antibody diversification to B-cell lymphomas and type-1 human immunodeficiency virus infectivity. During each of these processes, UNG2 recognizes uracilated DNA and excises the uracil base by flipping it into the enzyme active site. We have taken advantage of the extrahelical uracil recognition mechanism to build large small-molecule libraries in which uracil is tethered via flexible alkane linkers to a collection of secondary binding elements. This high-throughput synthesis and screening approach produced two novel uracil-tethered inhibitors of UNG2, the best of which was crystallized with the enzyme. Remarkably, this inhibitor mimics the crucial hydrogen bonding and electrostatic interactions previously observed in UNG2 complexes with damaged uracilated DNA. Thus, the environment of the binding site selects for library ligands that share these DNA features. This is a general approach to rapid discovery of inhibitors of enzymes that recognize extrahelical damaged bases

AID/APOBEC deaminases disfavor modified cytosines implicated in DNA demethylation

AID/APOBEC family cytosine deaminases, known to function in diverse cellular processes from antibody diversification to mRNA editing, have also been implicated in DNA demethylation, an important process for transcriptional activation. While oxidation-dependent pathways for demethylation have been described, pathways involving deamination of either 5-methylcytosine (mC) or 5-hydroxymethylcytosine (hmC) have emerged as alternatives. Here, we have addressed the biochemical plausibility of deamination-coupled demethylation. We found that purified AID/APOBECs have substantially reduced activity on mC relative to cytosine, their canonical substrate, and no detectable deamination of hmC. This finding was explained by the reactivity of a series of modified substrates, where steric bulk was increasingly detrimental to deamination. Further, upon AID/APOBEC overexpression, the deamination product of hmC was undetectable in genomic DNA, while oxidation intermediates remained detectable. Our results indicate that the steric requirements for cytosine deamination are one intrinsic barrier to the proposed function of deaminases in DNA demethylation

Transfer learning in a biomaterial fibrosis model identifies in vivo senescence heterogeneity and contributions to vascularization and matrix production across species and diverse pathologies

Cellular senescence is a state of permanent growth arrest that plays an important role in wound healing, tissue fibrosis, and tumor suppression. Despite senescent cells’ (SnCs) pathological role and therapeutic interest, their phenotype in vivo remains poorly defined. Here, we developed an in vivo–derived senescence signature (SenSig) using a foreign body response–driven fibrosis model in a p16-CreERT2;Ai14 reporter mouse. We identified pericytes and “cartilage-like” fibroblasts as senescent and defined cell type–specific senescence-associated secretory phenotypes (SASPs). Transfer learning and senescence scoring identified these two SnC populations along with endothelial and epithelial SnCs in new and publicly available murine and human data single-cell RNA sequencing (scRNAseq) datasets from diverse pathologies. Signaling analysis uncovered crosstalk between SnCs and myeloid cells via an IL34–CSF1R–TGFβR signaling axis, contributing to tissue balance of vascularization and matrix production. Overall, our study provides a senescence signature and a computational approach that may be broadly applied to identify SnC transcriptional profiles and SASP factors in wound healing, aging, and other pathologies.</p

Transfer learning in a biomaterial fibrosis model identifies in vivo senescence heterogeneity and contributions to vascularization and matrix production across species and diverse pathologies

Cellular senescence is a state of permanent growth arrest that plays an important role in wound healing, tissue fibrosis, and tumor suppression. Despite senescent cells’ (SnCs) pathological role and therapeutic interest, their phenotype in vivo remains poorly defined. Here, we developed an in vivo–derived senescence signature (SenSig) using a foreign body response–driven fibrosis model in a p16-CreERT2;Ai14 reporter mouse. We identified pericytes and “cartilage-like” fibroblasts as senescent and defined cell type–specific senescence-associated secretory phenotypes (SASPs). Transfer learning and senescence scoring identified these two SnC populations along with endothelial and epithelial SnCs in new and publicly available murine and human data single-cell RNA sequencing (scRNAseq) datasets from diverse pathologies. Signaling analysis uncovered crosstalk between SnCs and myeloid cells via an IL34–CSF1R–TGFβR signaling axis, contributing to tissue balance of vascularization and matrix production. Overall, our study provides a senescence signature and a computational approach that may be broadly applied to identify SnC transcriptional profiles and SASP factors in wound healing, aging, and other pathologies.</p

Transfer learning in a biomaterial fibrosis model identifies in vivo senescence heterogeneity and contributions to vascularization and matrix production across species and diverse pathologies

Cellular senescence is a state of permanent growth arrest that plays an important role in wound healing, tissue fibrosis, and tumor suppression. Despite senescent cells’ (SnCs) pathological role and therapeutic interest, their phenotype in vivo remains poorly defined. Here, we developed an in vivo–derived senescence signature (SenSig) using a foreign body response–driven fibrosis model in a p16-CreERT2;Ai14 reporter mouse. We identified pericytes and “cartilage-like” fibroblasts as senescent and defined cell type–specific senescence-associated secretory phenotypes (SASPs). Transfer learning and senescence scoring identified these two SnC populations along with endothelial and epithelial SnCs in new and publicly available murine and human data single-cell RNA sequencing (scRNAseq) datasets from diverse pathologies. Signaling analysis uncovered crosstalk between SnCs and myeloid cells via an IL34–CSF1R–TGFβR signaling axis, contributing to tissue balance of vascularization and matrix production. Overall, our study provides a senescence signature and a computational approach that may be broadly applied to identify SnC transcriptional profiles and SASP factors in wound healing, aging, and other pathologies.</p

Transfer learning in a biomaterial fibrosis model identifies in vivo senescence heterogeneity and contributions to vascularization and matrix production across species and diverse pathologies

Cellular senescence is a state of permanent growth arrest that plays an important role in wound healing, tissue fibrosis, and tumor suppression. Despite senescent cells’ (SnCs) pathological role and therapeutic interest, their phenotype in vivo remains poorly defined. Here, we developed an in vivo–derived senescence signature (SenSig) using a foreign body response–driven fibrosis model in a p16-CreERT2;Ai14 reporter mouse. We identified pericytes and “cartilage-like” fibroblasts as senescent and defined cell type–specific senescence-associated secretory phenotypes (SASPs). Transfer learning and senescence scoring identified these two SnC populations along with endothelial and epithelial SnCs in new and publicly available murine and human data single-cell RNA sequencing (scRNAseq) datasets from diverse pathologies. Signaling analysis uncovered crosstalk between SnCs and myeloid cells via an IL34–CSF1R–TGFβR signaling axis, contributing to tissue balance of vascularization and matrix production. Overall, our study provides a senescence signature and a computational approach that may be broadly applied to identify SnC transcriptional profiles and SASP factors in wound healing, aging, and other pathologies.</p