Biology subjects

Zhu, Z.

Publications and source records attributed to Zhu, Z..

At least 109 records · Page 6Linked to original sources

bioRxiv2025

Harnessing Uniform Design to Enhance AI-Driven Predictions of Physicochemical Properties of Short Peptides

Short peptides hold significant promise in drug discovery and materials science due to their biocompatibility, multifunctionality, and ease of synthesis. However, accurately predicting their physicochemical properties, a prerequisite for application development, remains a challenge. This study presents an innovative approach integrating uniform design (UD) with artificial intelligence (AI) to enhance prediction of key physicochemical properties, including aggregation propensity (AP), hydrophilicity (logP), and isoelectric point (pI). Using UD, we generate 31 distinct peptide datasets, with a consistent amino acid occupation fraction of 5% at each position, thereby creating unbiased training data for AI models. The performance of each AI model is rigorously evaluated using various testing schemes, and optimal sample sizes are determined for accurate prediction of each property. Additionally, Shapley Additive Explanations (SHAP) analysis identifies aromaticity, logP, net charge, and pI as the primary factors affecting peptide aggregation. This work provides comprehensive datasets on the physicochemical properties of all tetrapeptides, develops robust AI-based predictive models, and elucidates the relationships between key physicochemical characteristics and self-assembly behavior. By integrating experimental design, AI modeling, and peptide domain knowledge, our approach facilitates the discovery and optimization of functional peptides, offering new opportunities for peptide-based therapeutic applications.

bioinformatics↗

bioRxiv2025

The Caenorhabditis elegans spe-21 gene that encodes a palmitoyltransferase is necessary for spermiogenesis.

In most animals, spermatids that are produced must further differentiate into fertilization-competent spermatozoa after completing meiosis. In Caenorhabditis elegans, this process is known as spermiogenesis or spermatid activation and it results in the transformation of round, non-motile spermatids into amoeboid, motile spermatozoa. Spermatid activation in C. elegans is also associated with the fusion of Golgi-derived vesicles called the membranous organelles (MOs) with the plasma membrane. This fusion process is required for producing a fertilization-competent surface on the sperm by placing MO-carried, resident proteins onto the spermatozoon membrane. We have identified, cloned, and characterized the role of spe-21, also designated as dhhc-5, during both hermaphrodite and male spermatid activation. spe-21 null mutant worms are severely sub-fertile at all studied growth temperatures. spe-21 mutant spermatids fail to activate either in vivo or in vitro after treatment with known chemical activators. We have found that spe-21 is necessary for MO fusion and pseudopod formation in spermatids. The spe-21 gene encodes a predicted four pass transmembrane protein with a conserved Asp-His-His-Cys (DHHC) tetrapeptide zinc finger motif embedded in a cysteine rich region (DHHC-CRD type zinc finger motif). Generally, proteins with DHHC-CRD motifs catalyze the post-translational addition of palmitate to their protein substrates and are called palmitoyltransferases or palmitoylacyltransferases (PATs). We also found that mNeonGreen-tagged SPE-21 localizes to the MOs in spermatids. Together, our findings show that SPE-21 is an MO localized palmitoyltransferase required for proper spermatid activation and creation of fertilization-competent spermatozoa.

developmental biology↗

bioRxiv2025

Epigenome and interactome profiling uncovers principles of distal regulation in the barley genome

Regulation of transcription initiation is the ground level of modulating gene expression during plant development. This process relies on interactions between transcription factors and cis- regulatory elements (CREs), which become promising targets for crop bioengineering. To annotate CREs in the barley genome and understand mechanisms of distal regulation, we profiled several epigenetic features across three stages of barley embryo and leaves, and performed HiChIP to identify activating and repressive genomic interactions. Using machine learning, we integrated the data into seven chromatin states, predicting [~]77,000 CRE candidates, collectively representing 1.43% of the barley genome. Identified genomic interactions, often spanning multiple genes, linked thousands of CREs with their targets and revealed notably frequent promoter-promoter contacts. Using the LEA gene family as an example, we discuss possible roles of these interactions in transcription regulation. On the Vrn3 gene, we demonstrate the potential of our datasets to predict CREs for other developmental stages.

genomics↗

bioRxiv2025

SqueezeCall: Nanopore basecalling using a Squeezeformer network

Nanopore sequencing, a novel third-generation sequencing technique, offers significant advantages over other sequencing approaches, owing especially to its capabilities for direct RNA sequencing, real-time analysis, and long-read length. During nanopore sequencing, the sequencer measures changes in electrical current that occur as each nucleotide passes through the nanopores. A basecaller identifies the base sequences according to the raw current measurements. However, due to variations in DNA and RNA molecules, noise from the sequencing process, and limitations in existing methodology, accurate basecalling remains a challenge. In this paper, we introduce SqueezeCall, a novel approach that uses an end-to-end Squeezeformer-based model for accurate nanopore basecalling. In SqueezeCall, convolution layers are used to down sample raw signals and to model local dependencies. A Squeezeformer network is employed to capture the global context. Finally, a connectionist temporal classification (CTC) decoder generates the DNA sequence by a beam search algorithm. Inspired by the Wav2vec2.0 model, we masked a proportion of the time steps of the convolution outputs before feeding them to the Squeezeformer network and replaced them with a trained feature vector shared between all masked time steps. Experimental results demonstrate that this method enhances our models ability to resist noise and allows for improved basecalling accuracy. We trained SqueezeCall using a combination of three types of loss: CTC-CRF loss, intermediate CTC-CRF loss, and KL loss. Ablation experiments show that all three types of loss contribute to basecalling accuracy. Experiments on multiple species further demonstrate the potential of the Squeezeformer-based model to improve basecalling accuracy and its superiority over a recurrent neural network (RNN)-based model and Transformer-based models.

bioinformatics↗

bioRxiv2025

High-speed mapping of whole-mouse peripheral nerves at subcellular resolution

In contrast to the rapid advancements in mesoscale connectomic mapping of the mammalian brain, similar mapping the peripheral nervous system has remained challenging due to the bodys size and complexity. Here, we present a high-speed blockface volumetric imaging system with an optimized workflow of whole-body clearing, capable of imaging the entire adult mouse at micrometer resolution within 40 hours. Three-dimensional reconstruction of individual spinal fibers in Thy1-EGFP mice reveals distinct morphological features of sensory and motor projections along the ventral and dorsal rami. Immunostaining facilitates body-wide mapping of sympathetic nerves and their branches, highlighting their perivascular patterns in limb muscles, bones, and most visceral organs. Viral tracing elucidates the fine architecture of vagus nerves and individual vagal fibers, revealing unexpected projection routes to various organs. Our approach offers an effective means to achieve a holistic understanding of cellular-level interactions among different systems that underlie body physiology and disease. HighlightsO_LIImaging of whole adult mouse at uniform subcellular resolution within 40 hours C_LIO_LIReconstruction of 191 thoracic spinal neuron projections for Thy1-EGFP mice C_LIO_LIMapping of immunolabeled sympathetic projections and their perivascular patterns C_LIO_LIResolving virus-labeled architecture of vagus nerves and complex single-fiber routes C_LI

neuroscience↗

bioRxiv2025

Genome-wide Viral Nascent RNA Sequencing Unveils Polymerase Pausing Landscape at Single-nucleotide Precision

Understanding viral replication and transcription mechanisms is critical for developing effective antiviral strategies. The study of viral gene regulation in host cellular environment is an important bridge for translating mechanistic discoveries from in vitro studies to in vivo but it remains stagnated due to the absence of technological advancement. Current methods for studying viral transcription and replication have been limited to capturing only the mature viral RNAs, obscuring the dynamic intermediates and mechanistic details of these crucial processes. Here, we introduce an original technology we called "Total Elongating Nascent VIral Polymerase single-molecule Sequencing (TenVIP-seq)", which isolates and analyses newly synthesized RNA within the viral RNA-dependent RNA polymerase (RdRp) complex, enabling the discovery of mechanisms critical for both viral replication and transcription. Our first characterization of nascent RNA species for an RNA virus showed that RdRP exhibited non-random pausing with profile signatures along the eight influenza A virus (IAV) gene segments. We also revealed genome-wide pausing at known regulatory sites, such as the poly(U) tract polyadenylation site, and new putative regulatory sites at single-nucleotide resolution. Distinct pausing features between the viral genomic (vRNA) and anti-genomic (cRNA/mRNA) templates were observed, suggesting that RdRp processes transcription and replication differentially on positive and negative sense RNA. The NTP analog drug T-705 (favipiravir) intensified RdRp pauses during genome replication and transcription without introducing new pausing sites, while TRIM25 knockout in host cells infected with virus reduced RdRp pausing globally across the viral genome. Strikingly, we observed that terminal nucleotide misincorporations of nascent RNA sequencing of paused RdRP, which were previously undetectable, were as high as an average of 51.6% (vRNA) and 44.0% (cRNA/mRNA), suggesting that the mutational rate of viruses is much higher than previously thought. We demonstrated that TenVIP-seq holds potential in providing insights into the molecular mechanisms that control viral genome replication, gene expression and regulation, mutation, antiviral drug treatment, and virus-host interaction.

genetics↗

bioRxiv2025

Independent regulation of memory and emotion by selective retrieval

Selective retrieval of a target memory often triggers inhibitory control to reduce competition from related traces, a process that induces forgetting of the competing content. It is unknown, however, whether inhibition during selective retrieval specifically targets a competitors episodic representation or instead extends to its affective components. Here we report evidence in humans that selective retrieval of a neutral memory not only diminishes access to the mnemonic content of unpleasant competing memories, but also alters their emotional character. Memory and emotion suppression effects were accompanied by reduced neural activation and weakened representational patterns unique to competing memories in the VTC and amygdala respectively, in an independent fashion. Selective retrieval engaged the left VLPFC, which decreased in activity over repeated retrievals of the same memory, as competition from the unpleasant scene was resolved. This left VLPFC region colocalizes with key prefrontal regions engaged during cognitive reappraisal, suggesting that selective retrievals impact on affective responses may contribute to reappraisals benefits. These findings indicate that inhibitory control during selective retrieval affects both mnemonic and affective representations, providing a novel mechanistic basis for a well-known emotion regulation practice.

neuroscience↗

bioRxiv2024

Two neuropeptide signalings regulate post-mating refusal behavior and reproductive system in male crickets

After mating, insects always perform mating refusal behavior, termed post-mating refractoriness, due to physiological restrictions. Male crickets, Gryllus bimaculatus, characteristically exhibit 1-hour post-mating refractory stage, controlled by terminal abdominal ganglion. The molecular mechanisms underlying the male-specific precisely timed refractory stage remain elucidated. Here we show that among 28 neuropeptide precursors expressed in the terminal abdominal ganglion, DH31, myosuppressin, allatotropin, and sNPF exhibited male-specific expression based on RT-qPCR and in situ hybridization. However, RNA interference experiments showed that only knockdown of allatotropin and sNPF changed the duration of the refractoriness. Furthermore, allatotropin and sNPF knockdown influenced functions of male reproductive system by inhibiting seminal fluid secretion from male accessory gland and decreasing sperm storage in seminal vesicles, respectively. Knockdown of their receptors caused similar phenotypes. In conclusion, this study demonstrated the regulation of post-mating refusal behavior and reproductive system by Allatotropin and sNPF signalings in male crickets.

physiology↗

bioRxiv2024

HCN1 channels in GABAergic amygdalar neurons underpin male-biased aggressive behaviors

Aggression behaviors typically vary between sexes, but the molecular mechanisms driving these disparities in neural coding are unclear. We found that aggression selectively activates GABAergic neurons in the posterior substantia innominata (pSI), an extend amygdala region critical for aggressive behaviors in both sexes of mice, with males exhibiting higher neuronal activity during the attack. Utilizing single-nucleus RNA sequencing, we characterized the diverse molecular landscape of pSI neurons, revealing significant differences in ion channels and hormone regulator genes that may underpin sex-specific aggression. Male GABAergic pSI neurons exhibited remarkable hyperexcitability due to increased Ih currents. Strikingly, modulating HCN1 expression not only adjusted this hyperexcitability but also influenced sexual dimorphism in aggression: silencing HCN1 in the GABAergic pSI neurons reduced male aggression, while its overexpression markedly heightened aggression in females. Furthermore, testosterone was shown to intensify aggression by upregulating HCN1 and remodeling pSI circuits. These findings provide detailed sex-specific molecular mechanisms underlying social behaviors.

neuroscience↗

bioRxiv2024

STEP: Deciphering Spatial Atlas at Single-Cell Level with Whole-Transcriptome Coverage

Recent advances in spatial transcriptomics have revolutionized our understanding of tissue spatial architecture and biological processes. However, many of these technologies face significant challenges in achieving either single-cell resolution or comprehensive whole-transcriptome profiling, hindering their capacity to fully elucidate intercellular interactions and the tissue microenvironment. To address these limitations, we present STEP, a hybrid framework that synergistically integrates probabilistic models with deep learning techniques for spatial transcriptome analysis. Through innovations in model and algorithm design, STEP not only enhances sequencing-based spatial transcriptome data to single-cell resolution but accurately infers transcriptome-wide expression levels for image-based spatial transcriptomic. By leveraging the nuclear features extracted from histological images, STEP achieves precise predictions of cell type and gene expression and effectively diffuses the discriminative ability to serial sections for modeling solid tissue landscapes. The capability is particularly advantageous for analyzing cells with distinctive characteristics, such as cancer cells, enabling cross-sample inference. In addition, STEP simulates intercellular communication through a spatially resolved cell-cell interaction network, uncovering intrinsic biological processes. Overall, STEP equips researchers with a powerful tool for understanding biological functions and unveiling spatial gene expression patterns, paving the way for advancements in spatial transcriptomics research. Code is available at https://github.com/childishHU/STEP.

bioinformatics↗

bioRxiv2024

Reciprocal links between methionine metabolism, DNA repair and therapy resistance in glioblastoma

Glioblastoma (GBM) is uniformly lethal due to profound treatment resistance. Altered cellular metabolism is a key mediator of GBM treatment resistance. Uptake of the essential sulfur-containing amino acid methionine is drastically elevated in GBMs compared to normal cells, however, it is not known how this methionine is utilized or whether it relates to GBM treatment resistance. Here, we find that radiation acutely increases the levels of methionine-related metabolites in a variety of treatment-resistant GBM models. Stable isotope tracing studies further revealed that radiation acutely activates methionine to S-adenosyl methionine (SAM) conversion through an active signaling event mediated by the kinases of the DNA damage response. In vivo tumor SAM synthesis increases after radiation, while normal brain SAM production remains unchanged, indicating a tumor- specific metabolic alteration to radiation. Pharmacological and dietary strategies to block methionine to SAM conversion slowed DNA damage response and increased cell death following radiation in vitro. Mechanistically, these effects are due to depletion of DNA repair proteins and are reversed by SAM supplementation. These effects are selective to GBMs lacking the methionine salvage enzyme methylthioadenosine phosphorylase. Pharmacological inhibition of SAM synthesis hindered tumor growth in flank and orthotopic in vivo GBM models when combined with radiation. By contrast, methionine depletion does not reduce tumor SAM levels and fails to radiosensitize intracranial models, indicating depleting SAM, as opposed to simply lowering methionine, is critical for hindering tumor growth in intracranial models of GBM. These results highlight a new signaling link between DNA damage and SAM synthesis and define the metabolic fates of methionine in GBM in vivo. Inhibiting radiation-induced SAM synthesis slows DNA repair and augments radiation efficacy in GBM. Using MAT2A inhibitors to deplete SAM may selectively overcome treatment resistance in GBMs with defective methionine salvage while sparing normal brain.

cancer biology↗

bioRxiv2024

Squidiff: Predicting cellular development and responses to perturbations using a diffusion model

Single-cell sequencing has revolutionized our understanding of cellular heterogeneity and responses to environmental stimuli. However, mapping transcriptomic changes across diverse cell types in response to various stimuli and elucidating underlying disease mechanisms remains challenging. Studies involving physical stimuli, such as radiotherapy, or chemical stimuli, like drug testing, demand labor-intensive experimentation, hindering mechanistic insight and drug discovery. Here we present Squidiff, a diffusion model-based generative framework that predicts transcriptomic changes across diverse cell types in response to environmental changes. We demonstrate Squidiffs robustness across cell differentiation, gene perturbation, and drug response prediction. Through continuous denoising and semantic feature integration, Squidiff learns transient cell states and predicts high-resolution transcriptomic landscapes over time and conditions. Furthermore, we applied Squidiff to model blood vessel organoid development and cellular responses to neutron irradiation and growth factors. Our results demonstrate that Squidiff enables in silico screening of molecular landscapes, facilitating rapid hypothesis generation and providing valuable insights for precision medicine.

bioinformatics↗

bioRxiv2024

TLL1 knockdown attenuates prostate cancer progression by enhancing antitumor immunity

Due to the inevitable progression to castration-resistant prostate cancer (CRPC) following treatment with androgen deprivation therapy (ADT), it is essential to develop novel treatment approaches for managing CRPC. Here we showed that metalloproteinase TLL1 was positively associated with prostate cancer aggressiveness. Mechanistically, TLL1 promoted prostate cancer cells migration and metastasis through cleaving latent TGF-{beta}1 to activate TGF-{beta} signaling pathway. Moreover, LINC01179 interacted with Miz1 to attenuate TLL1 expression and LINC01179 impaired prostate cancer cell proliferation and migration ability by suppressing TLL1 expression to deactivate TGF-{beta} signaling activity. Meanwhile, we observed that TLL1 increased the expression of PD-L1 by activating TGF-{beta} signaling pathway and TLL1 depletion enhanced the antitumor efficacy by anti-PD-1 antibody via augmenting the infiltration proportions of CD8+ T cells in tumors. In addition, T cell-specific overexpression of TLL1 disrupted T cell development in the thymus. TLL1 overexpression in T cells accelerated RM-1 prostate tumor growth in mice by decreasing the infiltration of CD8+ T cells into tumors. Collectively, our results revealed that TLL1 may be a potential therapeutic target to alter prostate cancer progression.

cancer biology↗

bioRxiv2024

A general model for the seasonal to decadal dynamics of leaf area

Leaf phenology, represented at ecosystem scale by the seasonal dynamics of leaf area index (LAI), is a key control on the exchanges of CO2, energy and water between the land and atmosphere. Robust simulation of leaf phenology is thus important for both dynamic global vegetation models (DGVMs) and land-surface representations in climate and Earth System models. There is no general agreement on how leaf phenology should be modelled. However, a recent theoretical advance posits a universal relationship between the time course of "steady-state" gross primary production (GPP) and LAI - that is, the mutually consistent LAI and GPP that would pertain if weather conditions were held constant. This theory embodies the concept that leaves should be displayed when their presence is most beneficial to plants, combined with the reciprocal relationship of LAI and GPP via (a) the Beers law dependence of GPP on LAI, and (b) the requirement for GPP to support the allocation of carbon to leaves. Here we develop a global prognostic leaf phenology model, combining this theoretical approach with a parameter-sparse terrestrial GPP model (the P model) that achieves good fit to GPP derived from flux towers in all biomes, and a scheme based on the P model that predicts seasonal maximum LAI as the lesser of an energy-limited rate (maximizing GPP) and a water-limited rate (maximizing the use of available precipitation). The exponential moving average method is used to represent the time lag between leaf allocation and modelled steady-state LAI. The model captures satellite-derived LAI dynamics across biomes at both site and global levels. Since this model outperforms the 15 DGVMs used in the TRENDY project, it could provide a basis for improved representation of leaf-area dynamics in vegetation and climate models.

plant biology↗

bioRxiv2024

16S rRNA gene sequencing for bacterial identification and infectious disease diagnosis

16S rRNA gene sequence is the most common housekeeping genetic marker to study bacterial phylogeny and taxonomy. Therefore, 16S rRNA gene sequencing has the potential to identify novel bacteria and diagnose bacteria. This study compared 16S rRNA gene sequencing with conventional PCR for bacterial identification and disease diagnosis. The bacterial community in healthy and diseased hosts was analyzed by 16S rRNA gene sequencing. 16S rRNA gene sequencing is more sensitive than conventional PCR in detecting bacteria. Moreover, 16S rRNA gene sequencing is adequate to identify novel bacteria. 16S rRNA gene sequencing demonstrated that most pathogenic bacteria persist in diseased or healthy hosts in different abundance. Pathogenic bacteria, such as well-known chicken pathogen Avibacterium paragallinarum, Ornithobacterium rhinotracheale, and Gallibacterium anatis, were identified as indicator species of diseased samples. Alpha diversity analysis showed that the healthy group species is significantly higher than in the diseased groups. Beta diversity analysis also demonstrated differences between healthy and infected groups. The study concluded that 16S rRNA gene sequencing is a more sensitive method for detecting pathogens, and microbiota analysis can distinguish between healthy and diseased samples. Eventually, 16S rRNA gene sequencing has represented the potential in human and animal clinical diagnosis and novel bacterial identification.

microbiology↗

bioRxiv2024

Kinesin Autoinhibition Requires Elbow Phosphorylation

Kinesin motor proteins facilitate microtubule-based transport by converting chemical energy into mechanic forces, but this activity is autoinhibited until cargo is loaded. Regulatory mechanisms underlying this autoinhibitory conformation are not well understood. Here, we show that a NEver in mitosis Kinase NEKL-3 directly phosphorylates a flexible elbow region between two coiled coil domains connecting the motor head and tail of an intraflagellar transport kinesin, OSM-3. The phosphor dead (PD) mutation, but not phosphor mimic (PM) mutation, induce constitutive motility of OSM-3 in vitro. Using knock-in animals, we discovered that both PD and PM mutations shorten the C. elegans sensory cilia. The constitutively active OSM-3PD fails to enter cilia and abnormally accumulates in neurites, mimicking another hyperactive mutation, OSM-3G444E. Conversely, OSM-3PM enters cilia but moves at a reduced speed, indicating an inhibitory role of elbow phosphorylation in kinesin motility. These findings highlight the crucial role of elbow phosphorylation in regulating kinesin autoinhibition.

cell biology↗

bioRxiv2024

Change in brain molecular landscapes following electrical stimulation of the nucleus accumbens

Deep brain stimulation (DBS) targeting the nucleus accumbens (NAc) is a promising therapeutic intervention for treatment-resistant neuropsychiatric disorders such as depression, anxiety, and addiction. However, the molecular mechanisms underlying the clinical efficacy of NAc DBS remain largely unknown. One approach to address this question is by performing spatial gene expression analysis on cells located in different regions of the same circuit following NAc DBS. In this study, we utilized high-resolution spatial transcriptomics (Stereo-seq) to investigate gene expression changes induced by NAc DBS in the mouse brain. Mice were randomly allocated to received continuous electrical stimulation (0.1 mA, 130 Hz) or sham treatment (electrode implanted, no electrical stimulation given) for one week, and subsequent Stereo-seq analysis identified differentially expressed genes (DEGs) across various brain regions. Our findings reveal widespread alterations in synaptic function and neuronal connectivity, particularly in glutamate receptor-expressing neurons in the NAc, which play a key role in the reward circuitry. Functional enrichment analysis highlighted changes in transporter activity and glutamate receptor binding in brain regions such as the anterior cingulate cortex and lateral septal nucleus. Single-cell resolution mapping further identified key molecular players, including Nlgn1, Snca, PDE10a, and Syt1, which are critical for synaptic plasticity and neurotransmitter release, and have been implicated in various psychiatric disorders. These findings shed light on the molecular underpinnings of NAc DBS and provide insights into its therapeutic potential in modulating neural circuits associated with neuropsychiatric disorders.

molecular biology↗

bioRxiv2024

Novel derivatives of BCV and (S)-HPMPA inhibit orthopoxviruses and human adenoviruses more potently than BCV

BCV and tecovirimat are the only two chemical drugs that have been approved to treat smallpox and can be requested for Mpox treatment through a single-patient Emergency Investigational New Drug (EIND) application. Disappointedly, the efficacy of tecovirimat manifested in a recent clinical trial is far from being satisfactory, while the clinical efficacy of BCV is still inconclusive. Given that MPXV, variola and other emerging orthopoxviruses are posing serious threats to global health, it is urgent to develop better therapeutics. In this study, we tested the antiviral effects of three novel prodrugs, which were designed based on previously reported parent drugs, either (S)-HPMPC (cidofovir) or (S)-HPMPA. We found that one of the (S)-HPMPA-based prodrugs, ODE-(S)-HPMPA formate, exhibited significantly better anti-orthopoxvirus activity than BCV both in vitro and in vivo, which also inhibited human adenovirus type 2 and type 21 more efficiently than BCV. Most strikingly, the EC50 and EC90 of ODE-(S)-HPMPA formate against MPXV were more than 40-fold lower than those of BCV. In contrast, we observed that the anti-HSV-1 activities of the (S)-HPMPA-based prodrugs were less effective than those of the cidofovir-based prodrugs (BCV and BCV formate), especially in vivo. Moreover, we showed for the first time that cytidine and adenine analog combined therapies could provide mice with complete protection against lethal challenges of both vaccinia and HSV-1. Collectively, we propose that both the ODE-(S)-HPMPA formate and the BCV/ODE-(S)-HPMPA formate combination are worth further investigations for their potential clinical applications.

microbiology↗