Cytoplasmic DNA: sources, sensing, and role in aging and disease.

Endogenous cytoplasmic DNA (cytoDNA) species are emerging as key mediators of inflammation in diverse physiological and pathological contexts. Although the role of endogenous cytoDNA in innate immune activation is well established, the cytoDNA species themselves are often poorly characterized and difficult to distinguish, and their mechanisms of formation, scope of function and contribution to disease are incompletely understood. Here, we summarize current knowledge in this rapidly progressing field with emphases on similarities and differences between distinct cytoDNAs, their underlying molecular mechanisms of formation and function, interactions between cytoDNA pathways, and therapeutic opportunities in the treatment of age-associated diseases.

Eukaryotic DNA Replication Fork.

This review focuses on the biogenesis and composition of the eukaryotic DNA replication fork, with an emphasis on the enzymes that synthesize DNA and repair discontinuities on the lagging strand of the replication fork. Physical and genetic methodologies aimed at understanding these processes are discussed. The preponderance of evidence supports a model in which DNA polymerase ε (Pol ε) carries out the bulk of leading strand DNA synthesis at an undisturbed replication fork. DNA polymerases α and δ carry out the initiation of Okazaki fragment synthesis and its elongation and maturation, respectively. This review also discusses alternative proposals, including cellular processes during which alternative forks may be utilized, and new biochemical studies with purified proteins that are aimed at reconstituting leading and lagging strand DNA synthesis separately and as an integrated replication fork.

Ligand and Target Discovery by Fragment-Based Screening in Human Cells.

Advances in the synthesis and screening of small-molecule libraries have accelerated the discovery of chemical probes for studying biological processes. Still, only a small fraction of the human proteome has chemical ligands. Here, we describe a platform that marries fragment-based ligand discovery with quantitative chemical proteomics to map thousands of reversible small molecule-protein interactions directly in human cells, many of which can be site-specifically determined. We show that fragment hits can be advanced to furnish selective ligands that affect the activity of proteins heretofore lacking chemical probes. We further combine fragment-based chemical proteomics with phenotypic screening to identify small molecules that promote adipocyte differentiation by engaging the poorly characterized membrane protein PGRMC2. Fragment-based screening in human cells thus provides an extensive proteome-wide map of protein ligandability and facilitates the coordinated discovery of bioactive small molecules and their molecular targets.

Chemical Proteomics Identifies Druggable Vulnerabilities in a Genetically Defined Cancer.

The transcription factor NRF2 is a master regulator of the cellular antioxidant response, and it is often genetically activated in non-small-cell lung cancers (NSCLCs) by, for instance, mutations in the negative regulator KEAP1. While direct pharmacological inhibition of NRF2 has proven challenging, its aberrant activation rewires biochemical networks in cancer cells that may create special vulnerabilities. Here, we use chemical proteomics to map druggable proteins that are selectively expressed in KEAP1-mutant NSCLC cells. Principal among these is NR0B1, an atypical orphan nuclear receptor that we show engages in a multimeric protein complex to regulate the transcriptional output of KEAP1-mutant NSCLC cells. We further identify small molecules that covalently target a conserved cysteine within the NR0B1 protein interaction domain, and we demonstrate that these compounds disrupt NR0B1 complexes and impair the anchorage-independent growth of KEAP1-mutant cancer cells. Our findings designate NR0B1 as a druggable transcriptional regulator that supports NRF2-dependent lung cancers.

A ligation-independent sequencing method reveals tRNA-derived RNAs with blocked 3' termini.

Despite the numerous sequencing methods available, the diversity in RNA size and chemical modification makes it difficult to capture all RNAs in a cell. We developed a method that combines quasi-random priming with template switching to construct sequencing libraries from RNA molecules of any length and with any type of 3' modifications, allowing for the sequencing of virtually all RNA species. Our ligation-independent detection of all types of RNA (LIDAR) is a simple, effective tool to identify and quantify all classes of coding and non-coding RNAs. With LIDAR, we comprehensively characterized the transcriptomes of mouse embryonic stem cells, neural progenitor cells, mouse tissues, and sperm. LIDAR detected a much larger variety of tRNA-derived RNAs (tDRs) compared with traditional ligation-dependent sequencing methods and uncovered tDRs with blocked 3' ends that had previously escaped detection. Therefore, LIDAR can capture all RNAs in a sample and uncover RNA species with potential regulatory functions.

RNA:DNA hybrids from Okazaki fragments contribute to establish the Ku-mediated barrier to replication-fork degradation.

Nonhomologous end-joining (NHEJ) factors act in replication-fork protection, restart, and repair. Here, we identified a mechanism related to RNA:DNA hybrids to establish the NHEJ factor Ku-mediated barrier to nascent strand degradation in fission yeast. RNase H activities promote nascent strand degradation and replication restart, with a prominent role of RNase H2 in processing RNA:DNA hybrids to overcome the Ku barrier to nascent strand degradation. RNase H2 cooperates with the MRN-Ctp1 axis to sustain cell resistance to replication stress in a Ku-dependent manner. Mechanistically, the need of RNaseH2 in nascent strand degradation requires the primase activity that allows establishing the Ku barrier to Exo1, whereas impairing Okazaki fragment maturation reinforces the Ku barrier. Finally, replication stress induces Ku foci in a primase-dependent manner and favors Ku binding to RNA:DNA hybrids. We propose a function for the RNA:DNA hybrid originating from Okazaki fragments in controlling the Ku barrier specifying nuclease requirement to engage fork resection.

A pro-metastatic tRNA fragment drives Nucleolin oligomerization and stabilization of its bound metabolic mRNAs.

Stress-induced cleavage of transfer RNAs (tRNAs) into tRNA-derived fragments (tRFs) occurs across organisms from yeast to humans; yet, its mechanistic underpinnings and pathological consequences remain poorly defined. Small RNA profiling revealed increased abundance of a cysteine tRNA fragment (5'-tRFCys) during breast cancer metastatic progression. 5'-tRFCys was required for efficient breast cancer metastatic lung colonization and cancer cell survival. We identified Nucleolin as the direct binding partner of 5'-tRFCys. 5'-tRFCys promoted the oligomerization of Nucleolin and its bound metabolic transcripts Mthfd1l and Pafah1b1 into a higher-order transcript stabilizing ribonucleoprotein complex, which protected these transcripts from exonucleolytic degradation. Consistent with this, Mthfd1l and Pafah1b1 mediated pro-metastatic and metabolic effects downstream of 5'-tRFCys-impacting folate, one-carbon, and phosphatidylcholine metabolism. Our findings reveal that a tRF can promote oligomerization of an RNA-binding protein into a transcript stabilizing ribonucleoprotein complex, thereby driving specific metabolic pathways underlying cancer progression.

Caspase cleavage releases a nuclear protein fragment that stimulates phospholipid scrambling at the plasma membrane.

Phospholipid scrambling in dying cells promotes phosphatidylserine exposure, a critical process for efferocytosis. We previously identified the Xkr family protein Xkr4 as a phospholipid-scrambling protein, but its activation mechanisms remain unknown. Here we show that Xkr4 is activated in two steps: dimer formation by caspase-mediated cleavage and structural change caused by activating factors. To identify the factors, we developed a new screening system, "revival screening," using a CRISPR sgRNA library. Applying this system, we identified the nuclear protein XRCC4 as the single candidate for the Xkr4 activator. Upon apoptotic stimuli, XRCC4, contained in the DNA repair complex, is cleaved by caspases, and its C-terminal fragment with an intrinsically disordered region is released into the cytoplasm. Protein interaction screening showed that the fragment interacts directly with the Xkr4 dimer to activate it. This study demonstrates that caspase-mediated cleavage releases a nuclear protein fragment for direct regulation of lipid dynamics on the plasma membrane.

Replication gaps are a key determinant of PARP inhibitor synthetic lethality with BRCA deficiency.

Mutations in BRCA1 or BRCA2 (BRCA) is synthetic lethal with poly(ADP-ribose) polymerase inhibitors (PARPi). Lethality is thought to derive from DNA double-stranded breaks (DSBs) necessitating BRCA function in homologous recombination (HR) and/or fork protection (FP). Here, we report instead that toxicity derives from replication gaps. BRCA1- or FANCJ-deficient cells, with common repair defects but distinct PARPi responses, reveal gaps as a distinguishing factor. We further uncouple HR, FP, and fork speed from PARPi response. Instead, gaps characterize BRCA-deficient cells, are diminished upon resistance, restored upon resensitization, and, when exposed, augment PARPi toxicity. Unchallenged BRCA1-deficient cells have elevated poly(ADP-ribose) and chromatin-associated PARP1, but aberrantly low XRCC1 consistent with defects in backup Okazaki fragment processing (OFP). 53BP1 loss resuscitates OFP by restoring XRCC1-LIG3 that suppresses the sensitivity of BRCA1-deficient cells to drugs targeting OFP or generating gaps. We highlight gaps as a determinant of PARPi toxicity changing the paradigm for synthetic lethal interactions.

Control of noncoding RNA production and histone levels by a 5' tRNA fragment.

Small RNAs derived from mature tRNAs, referred to as tRNA fragments or "tRFs," are an emerging class of regulatory RNAs with poorly understood functions. We recently identified a role for one specific tRF-5' tRF-Gly-GCC, or tRF-GG-as a repressor of genes associated with the endogenous retroelement MERVL, but the mechanistic basis for this regulation was unknown. Here, we show that tRF-GG plays a role in production of a wide variety of noncoding RNAs-snoRNAs, scaRNAs, and snRNAs-that are dependent on Cajal bodies for stability and activity. Among these noncoding RNAs, regulation of the U7 snRNA by tRF-GG modulates heterochromatin-mediated transcriptional repression of MERVL elements by supporting an adequate supply of histone proteins. Importantly, the effects of inhibiting tRF-GG on histone mRNA levels, on activity of a histone 3' UTR reporter, and ultimately on MERVL regulation could all be suppressed by manipulating U7 RNA levels. We additionally show that the related RNA-binding proteins hnRNPF and hnRNPH bind directly to tRF-GG, and are required for Cajal body biogenesis, positioning these proteins as strong candidates for effectors of tRF-GG function in vivo. Together, our data reveal a conserved mechanism for 5' tRNA fragment control of noncoding RNA biogenesis and, consequently, global chromatin organization.

Fragment-based drug discovery supports drugging 'undruggable' protein-protein interactions.

Protein-protein interactions (PPIs) have important roles in various cellular processes, but are commonly described as 'undruggable' therapeutic targets due to their large, flat, featureless interfaces. Fragment-based drug discovery (FBDD) has achieved great success in modulating PPIs, with more than ten compounds in clinical trials. Here, we highlight the progress of FBDD in modulating PPIs for therapeutic development. Targeting hot spots that have essential roles in both fragment binding and PPIs provides a shortcut for the development of PPI modulators via FBDD. We highlight successful cases of cracking the 'undruggable' problems of PPIs using fragment-based approaches. We also introduce new technologies and future trends. Thus, we hope that this review will provide useful guidance for drug discovery targeting PPIs.

Fragment correlation mass spectrometry: Determining the structures of biopolymers in a complex mixture without isolating individual components.

Fragment correlation mass spectrometry correlates ion pairs generated from the same fragmentation pathway, achieved by covariance mapping of tandem mass spectra generated with an unmodified linear ion trap without preseparation. We enable the identification of different precursors at different charge states in a complex mixture from a large isolation window, empowering an analytical approach for data-independent acquisition. The method resolves and matches isobaric fragments, internal ions, and disulfide bond fragments. We suggest that this method represents a major advance for analyzing structures of biopolymers in mixtures.

Cooperative 2'-O-methylation of the wobble cytidine of human elongator tRNAMet(CAT) by a nucleolar and a Cajal body-specific box C/D RNP.

Site-specific 2'-O-ribose methylation of mammalian rRNAs and RNA polymerase II-synthesized spliceosomal small nuclear RNAs (snRNAs) is mediated by small nucleolar and small Cajal body (CB)-specific box C/D ribonucleoprotein particles (RNPs) in the nucleolus and the nucleoplasmic CBs, respectively. Here, we demonstrate that 2'-O-methylation of the C34 wobble cytidine of human elongator tRNAMet(CAT) is achieved by collaboration of a nucleolar and a CB-specific box C/D RNP carrying the SNORD97 and SCARNA97 box C/D 2'-O-methylation guide RNAs. Methylation of C34 prevents site-specific cleavage of tRNAMet(CAT) by the stress-induced endoribonuclease angiogenin, implicating box C/D guide RNPs in controlling stress-responsive production of putative regulatory tRNA fragments.

Beyond rRNA and snRNA: tRNA as a 2'-O-methylation target for nucleolar and Cajal body box C/D RNPs.

Box C/D small nucleolar RNAs (snoRNAs) and small Cajal body (CB) RNAs (scaRNAs) form ribonucleoprotein (RNP) complexes to mediate 2'-O-methylation of rRNAs and small nuclear RNAs (snRNAs), respectively. The site of methylation is determined by antisense elements in the box C/D RNAs that are complementary to sequences in target RNAs. However, numerous box C/D RNAs in mammalian cells lack antisense elements to rRNAs or snRNAs; thus, their targets remain unknown. In this issue of Genes & Development, Vitali and Kiss (pp. 741-746) demonstrate that "orphan" nucleolar box C/D snoRNA SNORD97 and CB box C/D scaRNA SCARNA97 contain antisense elements that target the wobble cytidine at position 34 of human elongator tRNAMet(CAT) for 2'-O-methylation (C34m). C34m is jointly mediated by SNORD97 and SCARNA97 despite their apparently different intranuclear locations. Furthermore, the investigators demonstrate that C34m prohibits site-specific cleavage of tRNAMet (CAT) into tRNA fragments (tRFs) by the stress-responsive endoribonuclease angiogenin, thereby uncovering a role for SNORD97 and SCARNA97 in the biogenesis of tRFs, which modulate a diverse set of cellular functions in human health and disease.

Enhancing clinical genomic accuracy with panelGC: a novel metric and tool for quantifying and monitoring GC biases in hybridization capture panel sequencing.

Accurate assessment of fragment abundance within a genome is crucial in clinical genomics applications such as the analysis of copy number variation (CNV). However, this task is often hindered by biased coverage in regions with varying guanine-cytosine (GC) content. These biases are particularly exacerbated in hybridization capture sequencing due to GC effects on probe hybridization and polymerase chain reaction (PCR) amplification efficiency. Such GC content-associated variations can exert a negative impact on the fidelity of CNV calling within hybridization capture panels. In this report, we present panelGC, a novel metric, to quantify and monitor GC biases in hybridization capture sequencing data. We establish the efficacy of panelGC, demonstrating its proficiency in identifying and flagging potential procedural anomalies, even in situations where instrument and experimental monitoring data may not be readily accessible. Validation using real-world datasets demonstrates that panelGC enhances the quality control and reliability of hybridization capture panel sequencing.

Precise and Predictable CRISPR Chromosomal Rearrangements Reveal Principles of Cas9-Mediated Nucleotide Insertion.

Chromosomal rearrangements including large DNA-fragment inversions, deletions, and duplications by Cas9 with paired sgRNAs are important to investigate genome structural variations and developmental gene regulation, but little is known about the underlying mechanisms. Here, we report that disrupting CtIP or FANCD2, which have roles in alternative non-homologous end joining, enhances precise DNA-fragment deletion. By analyzing the inserted nucleotides at the junctions of DNA-fragment editing of deletions, inversions, and duplications and characterizing the cleaved products, we find that Cas9 endonucleolytically cleaves the noncomplementary strand with a flexible scissile profile upstream of the -3 position of the PAM site in vivo and in vitro, generating double-strand break ends with 5' overhangs of 1-3 nucleotides. Moreover, we find that engineered Cas9 nucleases have distinct cleavage profiles. Finally, Cas9-mediated nucleotide insertions are nonrandom and are equal to the combined sequences upstream of both PAM sites with predicted frequencies. Thus, precise and predictable DNA-fragment editing could be achieved by perturbing DNA repair genes and using appropriate PAM configurations.

Deep Learning Prediction Boosts Phosphoproteomics-Based Discoveries Through Improved Phosphopeptide Identification.

Shotgun phosphoproteomics enables high-throughput analysis of phosphopeptides in biological samples. One of the primary challenges associated with this technology is the relatively low rate of phosphopeptide identification during data analysis. This limitation hampers the full realization of the potential offered by shotgun phosphoproteomics. Here we present DeepRescore2, a computational workflow that leverages deep learning-based retention time and fragment ion intensity predictions to improve phosphopeptide identification and phosphosite localization. Using a state-of-the-art computational workflow as a benchmark, DeepRescore2 increases the number of correctly identified peptide-spectrum matches by 17% in a synthetic dataset and identifies 19% to 46% more phosphopeptides in biological datasets. In a liver cancer dataset, 30% of the significantly altered phosphosites between tumor and normal tissues and 60% of the prognosis-associated phosphosites identified from DeepRescore2-processed data could not be identified based on the state-of-the-art workflow. Notably, DeepRescore2-processed data uniquely identifies EGFR hyperactivation as a new target in poor-prognosis liver cancer, which is validated experimentally. Integration of deep learning prediction in DeepRescore2 improves phosphopeptide identification and facilitates biological discoveries.

Iterative computational design and crystallographic screening identifies potent inhibitors targeting the Nsp3 macrodomain of SARS-CoV-2.

The nonstructural protein 3 (NSP3) of the severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) contains a conserved macrodomain enzyme (Mac1) that is critical for pathogenesis and lethality. While small-molecule inhibitors of Mac1 have great therapeutic potential, at the outset of the COVID-19 pandemic, there were no well-validated inhibitors for this protein nor, indeed, the macrodomain enzyme family, making this target a pharmacological orphan. Here, we report the structure-based discovery and development of several different chemical scaffolds exhibiting low- to sub-micromolar affinity for Mac1 through iterations of computer-aided design, structural characterization by ultra-high-resolution protein crystallography, and binding evaluation. Potent scaffolds were designed with in silico fragment linkage and by ultra-large library docking of over 450 million molecules. Both techniques leverage the computational exploration of tangible chemical space and are applicable to other pharmacological orphans. Overall, 160 ligands in 119 different scaffolds were discovered, and 153 Mac1-ligand complex crystal structures were determined, typically to 1 Å resolution or better. Our analyses discovered selective and cell-permeable molecules, unexpected ligand-mediated conformational changes within the active site, and key inhibitor motifs that will template future drug development against Mac1.

Differential molecular mechanisms of substrate recognition by selenium methyltransferases, INMT and TPMT, in selenium detoxification and excretion.

It is known that the recommended dietary allowance of selenium (Se) is dangerously close to its tolerable upper intake level. Se is detoxified and excreted in urine as trimethylselenonium ion (TMSe) when the amount ingested exceeds the nutritional level. Recently, we demonstrated that the production of TMSe requires two methyltransferases: thiopurine S-methyltransferase (TPMT) and indolethylamine N-methyltransferase (INMT). In this study, we investigated the substrate recognition mechanisms of INMT and TPMT in the Se-methylation reaction. Examination of the Se-methyltransferase activities of two paralogs of INMT, namely, nicotinamide N-methyltransferase and phenylethanolamine N-methyltransferase, revealed that only INMT exhibited Se-methyltransferase activity. Consistently, molecular dynamics simulations demonstrated that dimethylselenide was preferentially associated with the active center of INMT. Using the fragment molecular orbital method, we identified hydrophobic residues involved in the binding of dimethylselenide to the active center of INMT. The INMT-L164R mutation resulted in a deficiency in Se- and N-methyltransferase activities. Similarly, TPMT-R152, which occupies the same position as INMT-L164, played a crucial role in the Se-methyltransferase activity of TPMT. Our findings suggest that TPMT recognizes negatively charged substrates, whereas INMT recognizes electrically neutral substrates in the hydrophobic active center embedded within the protein. These observations explain the sequential requirement of the two methyltransferases in producing TMSe.

Characterization of alternate encounter assemblies of SARS-CoV-2 main protease.

The assembly of two monomeric constructs spanning segments 1-199 (MPro1-199) and 10-306 (MPro10-306) of SARS-CoV-2 main protease (MPro) was examined to assess the existence of a transient heterodimer intermediate in the N-terminal autoprocessing pathway of MPro model precursor. Together, they form a heterodimer population accompanied by a 13-fold increase in catalytic activity. Addition of inhibitor GC373 to the proteins increases the activity further by ∼7-fold with a 1:1 complex and higher order assemblies approaching 1:2 and 2:2 molecules of MPro1-199 and MPro10-306 detectable by analytical ultracentrifugation and native mass estimation by light scattering. Assemblies larger than a heterodimer (1:1) are discussed in terms of alternate pathways of domain III association, either through switching the location of helix 201 to 214 onto a second helical domain of MPro10-306 and vice versa or direct interdomain III contacts like that of the native dimer, based on known structures and AlphaFold 3 prediction, respectively. At a constant concentration of MPro1-199 with molar excess of GC373, the rate of substrate hydrolysis displays first order dependency on the MPro10-306 concentration and vice versa. An equimolar composition of the two proteins with excess GC373 exhibits half-maximal activity at ∼6 µM MPro1-199. Catalytic activity arises primarily from MPro1-199 and is dependent on the interface interactions involving the N-finger residues 1 to 9 of MPro1-199 and E290 of MPro10-306. Importantly, our results confirm that a single N-finger region with its associated intersubunit contacts is sufficient to form a heterodimeric MPro intermediate with enhanced catalytic activity.