Disrupting autorepression circuitry generates "open-loop lethality" to yield escape-resistant antiviral agents.

Across biological scales, gene-regulatory networks employ autorepression (negative feedback) to maintain homeostasis and minimize failure from aberrant expression. Here, we present a proof of concept that disrupting transcriptional negative feedback dysregulates viral gene expression to therapeutically inhibit replication and confers a high evolutionary barrier to resistance. We find that nucleic-acid decoys mimicking cis-regulatory sites act as "feedback disruptors," break homeostasis, and increase viral transcription factors to cytotoxic levels (termed "open-loop lethality"). Feedback disruptors against herpesviruses reduced viral replication >2-logs without activating innate immunity, showed sub-nM IC50, synergized with standard-of-care antivirals, and inhibited virus replication in mice. In contrast to approved antivirals where resistance rapidly emerged, no feedback-disruptor escape mutants evolved in long-term cultures. For SARS-CoV-2, disruption of a putative feedback circuit also generated open-loop lethality, reducing viral titers by >1-log. These results demonstrate that generating open-loop lethality, via negative-feedback disruption, may yield a class of antimicrobials with a high genetic barrier to resistance.

Immune Sensing of Synthetic, Bacterial, and Protozoan RNA by Toll-like Receptor 8 Requires Coordinated Processing by RNase T2 and RNase 2.

Human toll-like receptor 8 (TLR8) activation induces a potent T helper-1 (Th1) cell response critical for defense against intracellular pathogens, including protozoa. The receptor harbors two distinct binding sites, uridine and di- and/or trinucleotides, but the RNases upstream of TLR8 remain poorly characterized. We identified two endolysosomal endoribonucleases, RNase T2 and RNase 2, that act synergistically to release uridine from oligoribonucleotides. RNase T2 cleaves preferentially before, and RNase 2 after, uridines. Live bacteria, P. falciparum-infected red blood cells, purified pathogen RNA, and synthetic oligoribonucleotides all required RNase 2 and T2 processing to activate TLR8. Uridine supplementation restored RNA recognition in RNASE2-/- or RNASET2-/- but not RNASE2-/-RNASET2-/- cells. Primary immune cells from RNase T2-hypomorphic patients lacked a response to bacterial RNA but responded robustly to small-molecule TLR8 ligands. Our data identify an essential function of RNase T2 and RNase 2 upstream of TLR8 and provide insight into TLR8 activation.

Comprehensive in vivo secondary structure of the SARS-CoV-2 genome reveals novel regulatory motifs and mechanisms.

Severe-acute-respiratory-syndrome-related coronavirus 2 (SARS-CoV-2) is the positive-sense RNA virus that causes coronavirus disease 2019 (COVID-19). The genome of SARS-CoV-2 is unique among viral RNAs in its vast potential to form RNA structures, yet as much as 97% of its 30 kilobases have not been structurally explored. Here, we apply a novel long amplicon strategy to determine the secondary structure of the SARS-CoV-2 RNA genome at single-nucleotide resolution in infected cells. Our in-depth structural analysis reveals networks of well-folded RNA structures throughout Orf1ab and reveals aspects of SARS-CoV-2 genome architecture that distinguish it from other RNA viruses. Evolutionary analysis shows that several features of the SARS-CoV-2 genomic structure are conserved across ß-coronaviruses, and we pinpoint regions of well-folded RNA structure that merit downstream functional analysis. The native, secondary structure of SARS-CoV-2 presented here is a roadmap that will facilitate focused studies on the viral life cycle, facilitate primer design, and guide the identification of RNA drug targets against COVID-19.

In situ production and secretion of proteins endow therapeutic benefit against psoriasiform dermatitis and melanoma.

Genetic medicines have the potential to treat various diseases; however, certain ailments including inflammatory diseases and cancer would benefit from control over extracellular localization of therapeutic proteins. A critical gap therefore remains the need to develop and incorporate methodologies that allow for posttranslational control over expression dynamics, localization, and stability of nucleic acid-generated protein therapeutics. To address this, we explored how the body's endogenous machinery controls protein localization through signal peptides (SPs), including how these motifs could be incorporated modularly into therapeutics. SPs serve as a virtual zip code for mRNA transcripts that direct the cell where to send completed proteins within the cell and the body. Utilizing this signaling biology, we incorporated secretory SP sequences upstream of mRNA transcripts coding for reporter, natural, and therapeutic proteins to induce secretion of the proteins into systemic circulation. SP sequences generated secretion of various engineered proteins into the bloodstream following intravenous, intramuscular, and subcutaneous SP mRNA delivery by lipid, polymer, and ionizable phospholipid delivery carriers. SP-engineered etanercept/TNF-α inhibitor proteins demonstrated therapeutic efficacy in an imiquimod-induced psoriasis model by reducing hyperkeratosis and inflammation. An SP-engineered anti-PD-L1 construct mediated mRNA encoded proteins with longer serum half-lives that reduced tumor burden and extended survival in MC38 and B16F10 cancer models. The modular nature of SP platform should enable intracellular and extracellular localization control of various functional proteins for diverse therapeutic applications.

Fusion of FokI and catalytically inactive prokaryotic Argonautes enables site-specific programmable DNA cleavage.

Site-specific nucleases are crucial for genome engineering applications in medicine and agriculture. The ideal site-specific nucleases are easily reprogrammable, highly specific in target site recognition, and robust in nuclease activities. Prokaryotic Argonaute (pAgo) proteins have received much attention as biotechnological tools due to their ability to recognize specific target sequences without a protospacer adjacent motif, but their lack of intrinsic dsDNA unwinding activity limits their utility in key applications such as gene editing. Recently, we developed a pAgo-based system for site-specific DNA cleavage at physiological temperatures independently of the DNA form, using peptide nucleic acids (PNAs) to facilitate unwinding dsDNA targets. Here, we fused catalytically dead pAgos with the nuclease domain of the restriction endonuclease FokI and named this modified platform PNA-assisted FokI-(d)pAgo (PNFP) editors. In the PNFP system, catalytically inactive pAgo recognizes and binds to a specific target DNA sequence based on a programmable guide DNA sequence; upon binding to the target site, the FokI domains dimerize and introduce precise dsDNA breaks. We explored key parameters of the PNFP system including the requirements of PNA and guide DNAs, the specificity of PNA and guide DNA on target cleavage, the optimal concentration of different components, reaction time for invasion and cleavage, and ideal temperature and reaction buffer, to ensure efficient DNA editing in vitro. The results demonstrated robust site-specific target cleavage by PNFP system at optimal conditions in vitro. We envision that the PNFP system will provide higher editing efficiency and specificity with fewer off-target effects in vivo.

Nucleic acid hybridization-based detection of pathogenic RNA using microscale thermophoresis.

Infectious diseases are one of the world's leading causes of morbidity. Their rapid spread emphasizes the need for accurate and fast diagnostic methods for large-scale screening. Here, we describe a robust method for the detection of pathogens based on microscale thermophoresis (MST). The method involves the hybridization of a fluorescently labeled DNA probe to a target RNA and the assessment of thermophoretic migration of the resulting complex in solution within a 2 to 30-time window. We found that the thermophoretic migration of the nucleic acid-based probes is primarily determined by the fluorescent molecule used, rather than the nucleic acid sequence of the probe. Furthermore, a panel of uniformly labeled probes that bind to the same target RNA yields a more responsive detection pattern than a single probe, and moreover, can be used for the detection of specific pathogen variants. In addition, intercalating agents (ICA) can be used to alter migration directionality to improve detection sensitivity and resolving power by several orders of magnitude. We show that this approach can rapidly diagnose viral SARS-CoV2, influenza H1N1, artificial pathogen targets, and bacterial infections. Furthermore, it can be used for anti-microbial resistance testing within 2 h, demonstrating its diagnostic potential for early pathogen detection.

Accurately identifying nucleic-acid-binding sites through geometric graph learning on language model predicted structures.

The interactions between nucleic acids and proteins are important in diverse biological processes. The high-quality prediction of nucleic-acid-binding sites continues to pose a significant challenge. Presently, the predictive efficacy of sequence-based methods is constrained by their exclusive consideration of sequence context information, whereas structure-based methods are unsuitable for proteins lacking known tertiary structures. Though protein structures predicted by AlphaFold2 could be used, the extensive computing requirement of AlphaFold2 hinders its use for genome-wide applications. Based on the recent breakthrough of ESMFold for fast prediction of protein structures, we have developed GLMSite, which accurately identifies DNA- and RNA-binding sites using geometric graph learning on ESMFold predicted structures. Here, the predicted protein structures are employed to construct protein structural graph with residues as nodes and spatially neighboring residue pairs for edges. The node representations are further enhanced through the pre-trained language model ProtTrans. The network was trained using a geometric vector perceptron, and the geometric embeddings were subsequently fed into a common network to acquire common binding characteristics. Finally, these characteristics were input into two fully connected layers to predict binding sites with DNA and RNA, respectively. Through comprehensive tests on DNA/RNA benchmark datasets, GLMSite was shown to surpass the latest sequence-based methods and be comparable with structure-based methods. Moreover, the prediction was shown useful for inferring nucleic-acid-binding proteins, demonstrating its potential for protein function discovery. The datasets, codes, and trained models are available at https://github.com/biomed-AI/nucleic-acid-binding.

CLIP: accurate prediction of disordered linear interacting peptides from protein sequences using co-evolutionary information.

One of key features of intrinsically disordered regions (IDRs) is facilitation of protein-protein and protein-nucleic acids interactions. These disordered binding regions include molecular recognition features (MoRFs), short linear motifs (SLiMs) and longer binding domains. Vast majority of current predictors of disordered binding regions target MoRFs, with a handful of methods that predict SLiMs and disordered protein-binding domains. A new and broader class of disordered binding regions, linear interacting peptides (LIPs), was introduced recently and applied in the MobiDB resource. LIPs are segments in protein sequences that undergo disorder-to-order transition upon binding to a protein or a nucleic acid, and they cover MoRFs, SLiMs and disordered protein-binding domains. Although current predictors of MoRFs and disordered protein-binding regions could be used to identify some LIPs, there are no dedicated sequence-based predictors of LIPs. To this end, we introduce CLIP, a new predictor of LIPs that utilizes robust logistic regression model to combine three complementary types of inputs: co-evolutionary information derived from multiple sequence alignments, physicochemical profiles and disorder predictions. Ablation analysis suggests that the co-evolutionary information is particularly useful for this prediction and that combining the three inputs provides substantial improvements when compared to using these inputs individually. Comparative empirical assessments using low-similarity test datasets reveal that CLIP secures area under receiver operating characteristic curve (AUC) of 0.8 and substantially improves over the results produced by the closest current tools that predict MoRFs and disordered protein-binding regions. The webserver of CLIP is freely available at http://biomine.cs.vcu.edu/servers/CLIP/ and the standalone code can be downloaded from http://yanglab.qd.sdu.edu.cn/download/CLIP/.

Tetrahedral DNA loaded siCCR2 restrains M1 macrophage polarization to ameliorate pulmonary fibrosis in chemoradiation-induced murine model.

Idiopathic pulmonary fibrosis (IPF) is a chronic lethal disease in the absence of demonstrated efficacy for preventing progression. Although macrophage-mediated alveolitis is determined to participate in myofibrotic transition during disease development, the paradigm of continuous macrophage polarization is still under-explored due to lack of proper animal models. Here, by integrating 2.5 U/kg intratracheal Bleomycin administration and 10 Gy thorax irradiation at day 7, we generated a murine model with continuous alveolitis-mediated fibrosis, which mimics most of the clinical features of our involved IPF patients. In combination with data from scRNA-seq of patients and a murine IPF model, a decisive role of CCL2/CCR2 axis in driving M1 macrophage polarization was revealed, and M1 macrophage was further confirmed to boost alveolitis in leading myofibroblast activation. Multiple sticky-end tetrahedral framework nucleic acids conjunct with quadruple ccr2-siRNA (FNA-siCCR2) was synthesized in targeting M1 macrophages. FNA-siCCR2 successfully blocked macrophage accumulation in pulmonary parenchyma of the IPF murine model, thus preventing myofibroblast activation and leading to the disease remitting. Overall, our studies lay the groundwork to develop a novel IPF murine model, reveal M1 macrophages as potential therapeutic targets, and establish new treatment strategy by using FNA-siCCR2, which are highly relevant to clinical scenarios and translational research in the field of IPF.

Spherical nucleic acids as an infectious disease vaccine platform.

SignificanceUsing SARS-CoV-2 as a relevant case study for infectious disease, we investigate the structure-function relationships that dictate antiviral spherical nucleic acid (SNA) vaccine efficacy. We show that the SNA architecture can be rapidly employed to target COVID-19 through incorporation of the receptor-binding domain, and that the resulting vaccine potently activates human cells in vitro and mice in vivo. Furthermore, when challenged with a lethal viral infection, only mice treated with the SNA vaccine survived. Taken together, this work underscores the importance of rational vaccine design for infectious disease to yield vaccines that elicit more potent immune responses to effectively fight disease.

DNA-encoded library versus RNA-encoded library selection enables design of an oncogenic noncoding RNA inhibitor.

Nature evolves molecular interaction networks through persistent perturbation and selection, in stark contrast to drug discovery, which evaluates candidates one at a time by screening. Here, nature's highly parallel ligand-target search paradigm is recapitulated in a screen of a DNA-encoded library (DEL; 73,728 ligands) against a library of RNA structures (4,096 targets). In total, the screen evaluated ∼300 million interactions and identified numerous bona fide ligand-RNA three-dimensional fold target pairs. One of the discovered ligands bound a 5'GAG/3'CCC internal loop that is present in primary microRNA-27a (pri-miR-27a), the oncogenic precursor of microRNA-27a. The DEL-derived pri-miR-27a ligand was cell active, potently and selectively inhibiting pri-miR-27a processing to reprogram gene expression and halt an otherwise invasive phenotype in triple-negative breast cancer cells. By exploiting evolutionary principles at the earliest stages of drug discovery, it is possible to identify high-affinity and selective target-ligand interactions and predict engagements in cells that short circuit disease pathways in preclinical disease models.

Stem-loop formation drives RNA folding in mechanical unzipping experiments.

Accurate knowledge of RNA hybridization is essential for understanding RNA structure and function. Here we mechanically unzip and rezip a 2-kbp RNA hairpin and derive the 10 nearest-neighbor base pair (NNBP) RNA free energies in sodium and magnesium with 0.1 kcal/mol precision using optical tweezers. Notably, force-distance curves (FDCs) exhibit strong irreversible effects with hysteresis and several intermediates, precluding the extraction of the NNBP energies with currently available methods. The combination of a suitable RNA synthesis with a tailored pulling protocol allowed us to obtain the fully reversible FDCs necessary to derive the NNBP energies. We demonstrate the equivalence of sodium and magnesium free-energy salt corrections at the level of individual NNBP. To characterize the irreversibility of the unzipping-rezipping process, we introduce a barrier energy landscape of the stem-loop structures forming along the complementary strands, which compete against the formation of the native hairpin. This landscape correlates with the hysteresis observed along the FDCs. RNA sequence analysis shows that base stacking and base pairing stabilize the stem-loops that kinetically trap the long-lived intermediates observed in the FDC. Stem-loops formation appears as a general mechanism to explain a wide range of behaviors observed in RNA folding.

A single local delivery of paclitaxel and nucleic acids via an immunoactive polymer eliminates tumors and induces antitumor immunity.

Despite recent advances in cancer therapy, hard-to-reach, unidentified tumors remain a significant clinical challenge. A promising approach is to treat locatable and accessible tumors locally and stimulate antitumor immunity in situ to exert systemic effects against distant tumors. We hypothesize that a carrier of immunotherapeutics can play a critical role in activating antitumor immunity as an immunoadjuvant and a local retainer of drug combinations. Here, we develop a polyethyleneimine-lithocholic acid conjugate (2E'), which forms a hydrophobic core and cationic surface to codeliver hydrophobic small molecules and anionic nucleic acids and activates antigen-presenting cells via the intrinsic activities of 2E' components. 2E' delivers paclitaxel and small-interfering RNA (siRNA) targeting PD-L1 (or cyclic dinucleotide, [CDN]) to induce the immunogenic death of tumor cells and maintain the immunoactive tumor microenvironment, and further activates dendritic cells and macrophages, leveraging the activities of loaded drugs. A single local administration of 2E' or its combination with paclitaxel and PD-L1­targeting siRNA or CDN induces strong antitumor immunity, resulting in immediate regression of large established tumors, tumor-free survival, an abscopal effect on distant tumors, and resistance to rechallenge and metastasis in multiple models of murine tumors, including CT26 colon carcinoma, B16F10 melanoma, and 4T1 breast cancer. This study supports the finding that local administration of immunotherapeutics, when accompanied by the rationally designed carrier, can effectively protect the host from distant and recurrent diseases.

DNA Anchoring Strength Directly Correlates with Spherical Nucleic Acid-Based HPV E7 Cancer Vaccine Potency.

Vaccination for cancers arising from human papillomavirus (HPV) infection holds immense potential, yet clinical success has been elusive. Herein, we describe vaccination studies involving spherical nucleic acids (SNAs) incorporating a CpG adjuvant and a peptide antigen (E711-19) from the HPV-E7 oncoprotein. Administering the vaccine to humanized mice induced immunity-dependent on the oligonucleotide anchor chemistry (cholesterol vs (C12)9). SNAs containing a (C12)9-anchor enhanced IFN-γ production >200-fold, doubled memory CD8+ T-cell formation, and delivered more than twice the amount of oligonucleotide to lymph nodes in vivo compared to a simple admixture. Importantly, the analogous construct with a weaker cholesterol anchor performed similar to admix. Moreover, (C12)9-SNAs activated 50% more dendritic cells and generated T-cells cytotoxic toward an HPV+ cancer cell line, UM-SCC-104, with near 2-fold greater efficiency. These observations highlight the pivotal role of structural design, and specifically oligonucleotide anchoring strength (which correlates with overall construct stability), in developing efficacious therapeutic vaccines.

A DNA Molecular Logic Circuit for Precise Tumor Identification.

Tumor-associated antigens (TAAs) are not exclusively expressed in cancer cells, inevitably causing the "on target, off tumor" effect of molecular recognition tools. To achieve precise recognition of cancer cells, by using protein tyrosine kinase 7 (PTK7) as a model TAA, a DNA molecular logic circuit Aisgc8 was rationally developed by arranging H+-binding i-motif, ATP-binding aptamer, and PTK7-targeting aptamer Sgc8c in a DNA sequence. Aisgc8 output the conformation of Sgc8c to recognize PTK7 on cells in a simulated tumor microenvironment characterized by weak acidity and abundant ATP, but not in a simulated physiological environment. Through in vitro and in vivo results, Aisgc8 demonstrated its ability to precisely recognize cancer cells and, as a result, displayed excellent performance in tumor imaging. Thus, our studies produced a simple and efficient strategy to construct DNA logic circuits, opening new possibilities to develop convenient and intelligent precision diagnostics by using DNA logic circuits.

Selection and Interpretation of Molecular Diagnostics in Heart Transplantation.

The number of heart transplants performed annually in the United States and worldwide continues to increase, but there has been little change in graft longevity and patient survival over the past 2 decades. The reference standard for diagnosis of acute cellular and antibody-mediated rejection includes histologic and immunofluorescence evaluation of endomyocardial biopsy samples, despite invasiveness and high interrater variability for grading histologic rejection. Circulating biomarkers and molecular diagnostics have shown substantial predictive value in rejection monitoring, and emerging data support their use in diagnosing other posttransplant complications. The use of genomic (cell-free DNA), transcriptomic (mRNA and microRNA profiling), and proteomic (protein expression quantitation) methodologies in diagnosis of these posttransplant outcomes has been evaluated with varying levels of evidence. In parallel, growing knowledge about the genetically mediated immune response leading to rejection (immunogenetics) has enhanced understanding of antibody-mediated rejection, associated graft dysfunction, and death. Antibodies to donor human leukocyte antigens and the technology available to evaluate these antibodies continues to evolve. This review aims to provide an overview of biomarker and immunologic tests used to diagnose posttransplant complications. This includes a discussion of pediatric heart transplantation and the disparate rates of rejection and death experienced by Black patients receiving a heart transplant. This review describes diagnostic modalities that are available and used after transplant and the landscape of future investigations needed to enhance patient outcomes after heart transplantation.

DNA/RNA-based electrochemical nanobiosensors for early detection of cancers.

Nucleic acids, like DNA and RNA, serve as versatile recognition elements in electrochemical biosensors, demonstrating notable efficacy in detecting various cancer biomarkers with high sensitivity and selectivity. These biosensors offer advantages such as cost-effectiveness, rapid response, ease of operation, and minimal sample preparation. This review provides a comprehensive overview of recent developments in nucleic acid-based electrochemical biosensors for cancer diagnosis, comparing them with antibody-based counterparts. Specific examples targeting key cancer biomarkers, including prostate-specific antigen, microRNA-21, and carcinoembryonic antigen, are highlighted. The discussion delves into challenges and limitations, encompassing stability, reproducibility, interference, and standardization issues. The review suggests future research directions, exploring new nucleic acid recognition elements, innovative transducer materials and designs, novel signal amplification strategies, and integration with microfluidic devices or portable instruments. Evaluating these biosensors in clinical settings using actual samples from cancer patients or healthy donors is emphasized. These sensors are sensitive and specific at detecting non-communicable and communicable disease biomarkers. DNA and RNA's self-assembly, programmability, catalytic activity, and dynamic behavior enable adaptable sensing platforms. They can increase biosensor biocompatibility, stability, signal transduction, and amplification with nanomaterials. In conclusion, nucleic acids-based electrochemical biosensors hold significant potential to enhance cancer detection and treatment through early and accurate diagnosis.

Differential levels of circulating RNAs prior to endometrial cancer diagnosis.

Endometrial cancer (EC) is one of the most common female cancers and there is currently no routine screening strategy for early detection. An altered abundance of circulating microRNAs (miRNAs) and other RNA classes have the potential as early cancer biomarkers. We analyzed circulating RNA levels using small RNA sequencing, targeting RNAs in the size range of 17-47 nucleotides, in EC patients with samples collected prior to diagnosis compared to cancer-free controls. The analysis included 316 cases with samples collected 1-11 years prior to EC diagnosis, and 316 matched controls, both from the Janus Serum Bank cohort in Norway. We identified differentially abundant (DA) miRNAs, isomiRs, and small nuclear RNAs between EC cases and controls. The top EC DA miRNAs were miR-155-5p, miR-200b-3p, miR-589-5p, miR-151a-5p, miR-543, miR-485-5p, miR-625-p, and miR-671-3p. miR-200b-3p was previously reported to be among one of the top miRNAs with higher abundance in EC cases. We observed 47, 41, and 32 DA miRNAs for EC interacting with BMI, smoking status, and physical activity, respectively, including two miRNAs (miR-223-3p and miR-29b-3p) interacting with all three factors. The circulating RNAs are altered and show temporal dynamics prior to EC diagnosis. Notably, DA miRNAs for EC had the lowest q-value 4.39-6.66 years before diagnosis. Enrichment analysis of miRNAs showed that signaling pathways Fc epsilon RI, prolactin, toll-like receptor, and VEGF had the strongest associations.

Nucleic acid liquids.

The confluence of recent discoveries of the roles of biomolecular liquids in living systems and modern abilities to precisely synthesize and modify nucleic acids (NAs) has led to a surge of interest in liquid phases of NAs. These phases can be formed primarily from NAs, as driven by base-pairing interactions, or from the electrostatic combination (coacervation) of negatively charged NAs and positively charged molecules. Generally, the use of sequence-engineered NAs provides the means to tune microsopic particle properties, and thus imbue specific, customizable behaviors into the resulting liquids. In this way, researchers have used NA liquids to tackle fundamental problems in the physics of finite valence soft materials, and to create liquids with novel structured and/or multi-functional properties. Here, we review this growing field, discussing the theoretical background of NA liquid phase separation, quantitative understanding of liquid material properties, and the broad and growing array of functional demonstrations in these materials. We close with a few comments discussing remaining open questions and challenges in the field.

Prebiotic N-(2-Aminoethyl)-Glycine (AEG)-Assisted Synthesis of Proto-RNA?

Quantum mechanical calculations are used to explore the thermodynamics of possible prebiotic synthesis of the building blocks of nucleic acids. Different combinations of D-ribofuranose (Ribf) and N-(2-aminoethyl)-glycine (AEG) (trifunctional connectors (TCs)); the nature of the Ribf, its anomeric form, and its ring puckering (conformation); and the nature of the nucleobases (recognition units (RUs)) are considered. The combinatorial explosion of possible nucleosides has been drastically reduced on physicochemical grounds followed by a detailed thermodynamic evaluation of alternative synthetic pathways. The synthesis of nucleosides containing N-(2-aminoethyl)-glycine (AEG) is predicted to be thermodynamically favored suggesting a possible role of AEG as a component of an ancestral proto-RNA that may have preceded today's nucleic acids. A new pathway for the building of free nucleotides (exemplified by 5'-uridine monophosphate (UMP)) and of AEG dipeptides is proposed. This new pathway leads to a spontaneous formation of free UMP assisted by an AEG nucleoside in an aqueous environment. This appears to be a workaround to the "water problem" that prohibits the synthesis of nucleotides in water.