Biology subjects

Su, A.

Publications and source records attributed to Su, A..

At least 19 recordsLinked to original sources

bioRxiv2026

Adversity severity shapes caregiving predictors and neural correlates of infant social behavior

Early-life adversity is associated with highly variable developmental outcomes, but identifying sources of this heterogeneity is difficult because variation in outcome is typically accompanied by variation in exposure. Animal models provide experimental leverage by standardizing features of the early environment while allowing variation in developmental experience and outcome to remain observable. Using a graded limited bedding and nesting model spanning normative rearing, moderate restriction, and severe scarcity, we asked what distinguishes social outcomes among animals exposed to the same resource restriction. Severe scarcity increased adverse maternal handling while leaving organized nurturing behaviors intact. Following the P8-P12 rearing manipulation, pups were tested outside the home cage in a P13 social approach assay. Severe scarcity reduced the proportion of pups that approached the dam, but outcomes varied substantially among scarcity litters. Greater typical maternal pup transport predicted greater approach, whereas a greater proportion of rough transport predicted poorer approach. Transport composition did not differ across rearing conditions, but its relationship with social behavior did. Amygdala intercalated-cell recruitment also covaried with social approach under severe scarcity despite limited condition-level differences in regional c-Fos. Plasma corticosterone differed across rearing conditions but did not covary detectably with the principal caregiving, behavioral, or neural measures. Maternal transport and intercalated-cell recruitment were not robustly associated, identifying separable experiential and neural correlates of behavioral variation. These findings show that standardizing an environmental constraint does not produce uniform developmental experience or outcome, and that caregiving experiences preserved across rearing conditions can distinguish social outcomes under severe scarcity.

neuroscience↗

bioRxiv2026

Next-Generation Imipridones ONC206 and ONC212 Synergize with Lurbinectedin in Killing Pancreatic Ductal Adenocarcinoma Cells

Pancreatic ductal adenocarcinoma (PDAC) is a devastating malignancy with a five-year survival rate of approximately 13%, underscoring the urgent need for novel therapeutic strategies. Next-generation imipridones ONC206 and ONC212 are potent anticancer agents that activate the mitochondrial ClpP protease and the integrated stress response. Lurbinectedin, an FDA-approved therapy for metastatic small cell lung cancer, inhibits transcription by binding the DNA minor groove and has demonstrated preclinical efficacy in PDAC models. Here, we show that ONC206 and ONC212 are highly cytotoxic against PDAC cell lines as monotherapies and in combination with lurbinectedin. Both ONC206 and ONC212 achieved sub-micromolar seventy-two-hour IC values in BxPC-3, PANC-1, and HPAF-II PDAC cells, with ONC212 exhibiting greater potency across all lines. Mechanistically, ONC206 and ONC212 induce apoptosis through ClpX depletion, ATF4 induction, and caspase-mediated PARP cleavage. Combination treatment of lurbinectedin with both imipridones produced robust synergy, with ONC212 generally exhibiting stronger synergy at lower concentrations and HSA synergy scores up to 29.5. Importantly, these combinations showed minimal toxicity in CCD 841 CoN non-malignant colon epithelial cells, indicating selective tumor cell killing. Western blot analysis revealed that synergy between lurbinectedin and ONC212 is associated with upregulation of DR5 and downregulation of Bcl-2 and ClpX. These findings provide mechanistic and preclinical support for combining lurbinectedin with next-generation imipridones as a therapeutic strategy in PDAC.

cancer biology↗

bioRxiv2026

Rapid Intracellular Delivery of Human Heat Shock Protein 72 Inhibits Neurodegeneration and Oxidative Damage After a Traumatic Brain Injury

Fv-HSP72 is a rapid cell-penetrating human heat shock protein for the treatment of traumatic organ injuries. We have shown this re-engineered protein (HSP72) is capable of crossing the blood brain barrier (BBB) of rats suffering a controlled cortical impact (CCI) and remains in brain tissue for up to 12 hours; long after clearance from the cortex of uninjured rats. Peptide sequences unique to Fv-HSP72 allow for its differential detection from endogenous HSP72. Male Sprague-Dawley rats were divided into 10 groups of n=10 with those animals receiving a CCI subjected to a unilateral cortical contusion simulating a moderate to severe brain injury using an electronically controlled pneumatic impact device. Control groups were either uninjured (Sham), injured (TBI Only), or injured and given buffer (TBI+Vehicle). Rats treated with one of three Fv-HSP72 variants were dosed at 10 or 30mg/kg 15m post-impact, then sacrificed 48 hours later. Cortical tissues were extracted from the ipsilateral and contralateral hemispheres for biomarker analysis. Here we report results of our drug inhibiting neurodegeneration based on five biomarkers (NF-L, pNF-H, pTau [T181, T231, S396]). These results were statistically significant, especially for one of the Fv-HSP72 variants, when comparing differences both between treatment groups and within groups (i.e. when comparing ipsi-vs. contralateral hemispheres). Significant inhibition of oxidative stress (3-NT) and inflammatory (IL-6) biomarkers were also observed (both p<0.0001). With similar results obtained for a blast injury model being published elsewhere, the analyses suggest Fv-HSP72 is neuroprotective following a direct impact brain injury. One sentence summaryThis study describes the effectiveness of a biologic agent, Fv-HSP72, in significantly inhibiting neuronal tissue damage in the brain when administered after a direct cortical impact.

neuroscience↗

bioRxiv2025

Predicting the structures of cyclic peptides containing unnatural amino acids by HighFold2

Cyclic peptides containing unnatural amino acids possess many excellent properties and have become promising candidates in drug discovery. Therefore, accurately predicting the three-dimensional structures of cyclic peptides containing unnatural residues will significantly advance the development of cyclic peptide-based therapeutics. Although deep learning-based structural prediction models have made tremendous progress, these models still cannot predict the structures of cyclic peptides containing unnatural amino acids. To address this gap, we introduce a novel model, HighFold2, built upon the AlphaFold-Multimer framework. HighFold2 first extends the pre-defined rigid groups and their initial atomic coordinates from natural amino acids to unnatural amino acids, thus enabling structural prediction for these residues. Then, it incorporates an additional neural network to characterize the atom-level features of peptides, allowing for multi-scale modeling of peptide molecules while enabling the distinction between various unnatural amino acids. Besides, HighFold2 constructs a relative position encoding matrix for cyclic peptides based on different cyclization constraints. Except for training using spatial structures with unnatural amino acids, HighFold2 also parameterizes the unnatural amino acids to relax the predicted structure by energy minimization for clash elimination. Extensive empirical experiments demonstrate that HighFold2 can accurately predict the three-dimensional structures of cyclic peptide monomers containing unnatural amino acids and their complexes with proteins, with the median RMSD for C reaching 1.891 [A]. All these results indicate the effectiveness of HighFold2, representing a significant advancement in cyclic peptide-based drug discovery.

bioinformatics↗

bioRxiv2024

Single-cell Organelle Extraction with Cellular Indexing

Bulk methods to fractionate organelles lack the resolution to capture single-cell heterogeneity. While microfluidic approaches attempt to fractionate organelles at the cellular level, they fail to map each organelle back to its cell of origin--crucial for multiomics applications. To address this, we developed VacTrap, a high-throughput microfluidic device for isolating and spatially indexing single nuclei from mammalian cells. VacTrap consists of three aligned layers: (1) a Bis-gel microwells layer with a trapdoors (BAC-gel) base, fabricated atop a through-hole glass slide; (2) a PDMS microwell layer to receive transferred nuclei; and (3) a vacuum manifold. VacTrap operation begins with cell lysis using DDF to release intact nuclei into the Bis-gel microwells, while cytoplasmic proteins are electrophoresed into the Bis-gel. Upon exposure to DTT and vacuum force, the trapdoors open, allowing nuclei to transfer to the PDMS microwells. VacTrap dissolves the trapdoors within 3-5 minutes and achieve synchronized nuclei transfer with 98% efficiency across 80% of trapdoors in a 256-microwell array, surpassing the <1% efficiency of passive transfer without vacuum. Morphology analysis confirmed preservation of organelle integrity throughout VacTrap operation. By enabling spatial indexing of nuclei back to their original cell, VacTrap provides a robust, high-throughput tool for single-cell multiomics applications.

bioengineering↗

bioRxiv2024

NCPepFold: Accurate Prediction of Non-canonical Cyclic Peptide Structures via Cyclization Optimization with Multigranular Representation

Artificial intelligence-based peptide structure prediction methods have revolutionized biomolecular science. However, restricting predictions to peptides composed solely of 20 natural amino acids significantly limits their practical application, as such peptides often demonstrate poor stability under physiological conditions. Here, we present NCPepFold, a computational approach that can utilize a specific cyclic position matrix to directly predict the structure of cyclic peptides with non-canonical amino acids. By integrating multi-granularity information at the residue- and atomic-level, along with fine-tuning techniques, NCPepFold significantly improves prediction accuracy, with the average peptide RMSD for cyclic peptides being 1.640 [A]. In summary, this is a novel deep learning model designed specifically for cyclic peptides with non-canonical amino acids without length restrictions, offering great potential for peptide drug design and advancing biomedical research.

bioinformatics↗

bioRxiv2024

The single-cell spatial landscape of stage III colorectal cancers

We conducted a spatial analysis using imaging mass cytometry applied to stage III colorectal adenocarcinomas. This study used multiplexed markers to distinguish individual cells and their spatial organization from 52 colorectal cancers. We determined the landscape features of cellular spatial features in the CRC tumor microenvironment. This spatial single-cell analysis identified 10 unique cell phenotypes in the tumor microenvironment that included stromal and immune cells with a subset which had a proliferative phenotype. These special features included spatial neighborhood interactions between single cells as well as different tissue niches, especially the tumor infiltrating lymphocyte regions. We applied a robust statistical analysis to identify significant correlations of cell features with phenotypes such as microsatellite instability or recurrence. We determined that microsatellite stable (MSS) colorectal cancers had an increased risk of recurrence if they had the following features: 1) a low level of stromal tumor-infiltrating lymphocytes, and 2) low interactions between CD4+ T cells and stromal cells. Our results point to the utility of spatial single-cell interaction analysis in defining novel features of the tumor immune microenvironments and providing useful clinical cell-related spatial biomarkers.

cancer biology↗

bioRxiv2023

Acetylcholine promotes directionally biased glutamatergic retinal waves

Spontaneous retinal waves are a critical driving force for the self-organization of the mouse visual system prior to eye-opening. Classically characterized as taking place in three distinct stages defined by their primary excitatory drive, Stage II waves during the first postnatal week are propagated through the volume transmission of acetylcholine while Stage III retinal waves during the second postnatal week depend on glutamatergic transmission from bipolar cells. However, both late Stage II and early Stage III retinal waves share a defining propagation bias toward the temporal-to-nasal direction despite developmental changes in the underlying cholinergic and glutamatergic retinal networks. Here, we leverage genetic and pharmacological manipulations to investigate the relationship between cholinergic and glutamatergic neurotransmission during the transition between Stage II and Stage III waves in vivo. We find that the cholinergic network continues to play a vital role in the propagation of waves during Stage III after the primary mode of neurotransmission changes to glutamate. In the absence of glutamatergic waves, compensatory cholinergic activity persists but lacks the propagation bias typically observed in Stage III waves. In the absence of cholinergic waves, gap junction-mediated activity typically associated with Stage I waves persists throughout the developmental window in which Stage III waves usually emerge and lacks the spatiotemporal profile of normal Stage III waves, including a temporal-to-nasal propagation bias. Finally, we show that cholinergic signaling through {beta}2 subunit-containing nicotinic acetylcholine receptors, essential for Stage II wave propagation, is also critical for Stage III wave directionality.

neuroscience↗

bioRxiv2023

Phospholipid isotope tracing reveals β-catenin-driven suppression of phosphatidylcholine metabolism in hepatocellular carcinoma

Background and AimsActivating mutations in the CTNNB1 gene encoding {beta}-catenin are among the most frequently observed oncogenic alterations in hepatocellular carcinoma (HCC). HCC with CTNNB1 mutations show profound alterations in lipid metabolism including increases in fatty acid oxidation and transformation of the phospholipidome, but it is unclear how these changes arise and whether they contribute to the oncogenic program in HCC. MethodsWe employed untargeted lipidomics and targeted isotope tracing to quantify phospholipid production fluxes in an inducible human liver cell line expressing mutant {beta}-catenin, as well as in transgenic zebrafish with activated {beta}-catenin-driven HCC. ResultsIn both models, activated {beta}-catenin expression was associated with large changes in the lipidome including conserved increases in acylcarnitines and ceramides and decreases in triglycerides. Lipid flux analysis in human cells revealed a large reduction in phosphatidylcholine (PC) production rates as assayed by choline tracer incorporation. We developed isotope tracing lipid flux analysis for zebrafish and observed similar reductions in phosphatidylcholine synthesis flux accomplished by sex-specific mechanisms. ConclusionsThe integration of isotope tracing with lipid abundances highlights specific lipid class transformations downstream of {beta}-catenin signaling in HCC and suggests future HCC-specific lipid metabolic targets. SynopsisIn this work, we show by lipid specific isotope tracing that mutations in the oncogene CTNNB1 leads to conserved changes in lipid metabolism in hepatocellular carcinoma. These include the stimulation of fatty acid oxidation and a suppression of phosphorylcholine synthesis.

cancer biology↗

bioRxiv2023

A spatially mapped gene expression signature for intestinal stem-like cells identifies high-risk precursors of gastric cancer

ObjectiveGastric intestinal metaplasia (GIM) is a precancerous lesion that increases gastric cancer (GC) risk. The Operative Link on GIM (OLGIM) is a combined clinical-histopathologic system to risk-stratify patients with GIM. The identification of molecular biomarkers that are indicators for advanced OLGIM lesions may improve cancer prevention efforts. MethodsThis study was based on clinical and genomic data from four cohorts: 1) GAPS, a GIM cohort with detailed OLGIM severity scoring (N=303 samples); 2) the Cancer Genome Atlas (N=198); 3) a collation of in-house and publicly available scRNA-seq data (N=40), and 4) a spatial validation cohort (N=5) consisting of annotated histology slides of patients with either GC or advanced GIM. We used a multi-omics pipeline to identify, validate and sequentially parse a highly-refined signature of 26 genes which characterize high-risk GIM. ResultsUsing standard RNA-seq, we analyzed two separate, non-overlapping discovery (N=88) and validation (N=215) sets of GIM. In the discovery phase, we identified 105 upregulated genes specific for high-risk GIM (defined as OLGIM III-IV), of which 100 genes were independently confirmed in the validation set. Spatial transcriptomic profiling revealed 36 of these 100 genes to be expressed in metaplastic foci in GIM. Comparison with bulk GC sequencing data revealed 26 of these genes to be expressed in intestinal-type GC. Single-cell profiling resolved the 26-gene signature to both mature intestinal lineages (goblet cells, enterocytes) and immature intestinal lineages (stem-like cells). A subset of these genes was further validated using single-molecule multiplex fluorescence in situ hybridization. We found certain genes (TFF3 and ANPEP) to mark differentiated intestinal lineages, whereas others (OLFM4 and CPS1) localized to immature cells in the isthmic/crypt region of metaplastic glands, consistent with the findings from scRNAseq analysis. Conclusionsusing an integrated multi-omics approach, we identified a novel 26-gene expression signature for high-OLGIM precursors at increased risk for GC. We found this signature localizes to aberrant intestinal stem-like cells within the metaplastic microenvironment. These findings hold important translational significance for future prevention and early detection efforts.

cancer biology↗

bioRxiv2023

IN SITU IMAGING OF RETINAL CALCIUM DYNAMICS IN AWAKE ANIMALS

Mammalian vision starts in the retina. The study of retinal circuits in vivo is essential for comprehending retinal neural dynamics under physiological conditions. While several transpupillary retina imaging techniques have been utilized in anesthetized animals, the in situ imaging of retinal activity in awake animals has been more difficult to accomplish. These limits have frustrated crucial scientific inquiries, such as how visual processing in the retina is modulated by behavior. In this study, we present novel experimental approaches that stabilize the eye to access in situ retinal dynamics with optical techniques in awake mice. Our findings demonstrate that this method can be utilized to: 1) image neural activity in distinct cell types across multiple ages, 2) record meso-scale (e.g. spontaneous retinal waves) or cellular retinal dynamics, 3) study retina functional connectivity in vivo, and 4) pharmacologically manipulate retinal activity. We applied these novel approaches to demonstrate that retinal activity is strongly modulated by movement through H1R-dependent histaminergic transmission in vivo, even at the amacrine cell level. These methods are suitable to simultaneously record retinal and brain activity dynamics or to investigate retinal responses to patterned visual stimuli, making accessible fundamental questions about visual processing that have previously been very challenging to achieve.

neuroscience↗

bioRxiv2022

Long-range inhibitory neurons mediate cortical neurovascular coupling

Neuronal activity evokes a vascular response that is essential to sustain brain function. We show that neurovascular coupling (NVC) is mediated by long-range projecting GABAergic neurons that express Tacr1. Whisker stimulation elicited Tacr1 neuron activity in the barrel cortex through feed-forward excitatory pathways. Optogenetic activation of Tacr1 neurons elicited vasodilation, whereas inhibition significantly reduced whisker-evoked hemodynamic responses. Moreover, vasodilation was preceded by capillary pericyte activity, demonstrating a mechanism for NVC.

neuroscience↗

bioRxiv2021

A Deep Learning Model for Molecular Label Transfer that Enables Cancer Cell Identification from Histopathology Images

Deep learning cancer classification systems have the potential to improve cancer diagnosis. However, development of these computational approaches depends on prior annotation through a pathologist. This initial step relying on a manual, low-resolution, time-consuming process is highly variable and subject to observer variance. To address this issue, we developed a novel method, H&E Molecular neural network (HEMnet). This two-step process utilises immunohistochemistry as an initial molecular label for cancer cells on a H&E image and then we train a cancer classifier on the overlapping clinical histopathological images. Using this molecular transfer method, we show that HEMnet accurately distinguishes colorectal cancer from normal tissue at high resolution without the need for an initial manual histopathologic evaluation. Our validation study using histopathology images from TCGA samples accurately estimates tumour purity. Overall, our method provides a path towards a fully automated delineation of any type of tumor so long as there is a cancer-oriented molecular stain available for subsequent learning. Software, tutorials and interactive tools are available at: https://github.com/BiomedicalMachineLearning/HEMnet

bioinformatics↗

bioRxiv2020

Pseudouridine synthases modify human pre-mRNA co-transcriptionally and affect splicing

Eukaryotic messenger RNAs are extensively decorated with modified nucleotides and the resulting epitranscriptome plays important regulatory roles in cells 1. Pseudouridine ({Psi}) is a modified nucleotide that is prevalent in human mRNAs and can be dynamically regulated 2-5. However, it is unclear when in their life cycle RNAs become pseudouridylated and what the endogenous functions of mRNA pseudouridylation are. To determine if pseudouridine is added co-transcriptionally, we conducted pseudouridine profiling 2 on chromatin-associated RNA to reveal thousands of intronic pseudouridines in nascent pre-mRNA at locations that are significantly associated with alternatively spliced exons, enriched near splice sites, and overlap hundreds of binding sites for regulatory RNA binding proteins. Multiple distinct pseudouridine synthases with tissue-specific expression pseudouridylate pre-mRNA sites, and genetic manipulation of the predominant pre-mRNA modifying pseudouridine synthases PUS1, PUS7 and RPUSD4 induced widespread changes in alternative splicing in cells, supporting a role for pre-mRNA pseudouridylation in alternative splicing regulation. Consistently, we find that individual pseudouridines identified in cells are sufficient to directly affect splicing in vitro. Together with previously observed effects of artificial pseudouridylation on RNA-RNA6-8 and RNA-protein 9-11 interactions that are relevant for splicing, our results demonstrate widespread co-transcriptional pre-mRNA pseudouridylation and establish the enormous potential for this RNA modification to control human gene expression.

molecular biology↗

bioRxiv2020

Targeting serine hydroxymethyltransferases 1 and 2 for T-cell acute lymphoblastic leukemia therapy.

Despite progress in the treatment of acute lymphoblastic leukemia (ALL), T-cell ALL (T-ALL) has limited treatment options particularly in the setting of relapsed/refractory disease. Using an unbiased genome-scale CRISPR-Cas9 screen we sought to identify pathway dependencies for T-ALL which could be harnessed for therapy development. Disruption of the one-carbon folate, purine and pyrimidine pathways scored as the top metabolic pathways required for T-ALL proliferation. We used a recently developed inhibitor of SHMT1 and SHMT2, RZ-2994, to characterize the effect of inhibiting these enzymes of the one-carbon folate pathway in T-ALL and found that T-ALL cell lines were differentially sensitive to RZ-2994, with a S/G2 cell cycle arrest. The effects of SHMT1/2 inhibition were rescued by formate supplementation. Loss of both SHMT1 and SHMT2 was necessary for impaired growth and cell cycle arrest, with suppression of both SHMT1 and SHMT2 impairing leukemia progression in vivo. RZ-2994 decreased leukemia burden in vivo and remained effective in the setting of methotrexate resistance in vitro. This study highlights the significance of the one-carbon folate pathway in T-ALL and supports further development of SHMT inhibitors for treatment of T-ALL and other cancers.

cancer biology↗

bioRxiv2019

SpaCell: integrating tissue morphology and spatial gene expression to predict disease cells

MotivationSpatial transcriptomics technology is increasingly being applied because it enables the measurement of spatial gene expression in an intact tissue along with imaging morphology of the same tissue. However, current analysis methods for spatial transcriptomics data do not use image pixel information, thus missing the quantitative links between gene expression and tissue morphology.\n\nResultsWe developed an user-friendly deep learning software, SpaCell, to integrate millions of pixel intensity values with thousands of gene expression measurements from spatially-barcoded spots in a tissue. We show the integration approach outperforms the use of gene count alone or imaging data alone to create deep learning models to identify cell types or predict labels of tissue images with high resolution and accuracy.\n\nAvailabilityThe SpaCell package is open source under a MIT license and it is available at https://github.com/BiomedicalMachineLearning/SpaCell\n\nContactquan.nguyen@uq.edu.au

bioinformatics↗

bioRxiv2018

Association study of long-term kidney transplant rejection using whole-exome sequencing

Long-term renal allograft rejection is the most common outcome in kidney transplantation. Continuing the crusade to extend allograft function after the first year post-transplantation, we attempted to associate genetic factors that might contribute to long-term allograft outcomes by sequencing the exomes of patients diagnosed with chronic allograft nephropathy/interstitial fibrosis and tubular atrophy. A variety of association analyses were employed, but these analyses failed to identify statistically significant associations. The study was underpowered to detect the association of rare genomic variants with small effect sizes. However, it confirmed previous reports of the absence of large effects from common variants. We have made both the study data and analysis workflow available for public use, and we hope that these resources will help to power future meta-analyses that may detect smaller effects.

genetics↗

bioRxiv2018

Development of whole-porcine monoclonal antibodies with potent neutralization activity against classical swine fever virus (CSFV) from single B cells

Classical swine fever (CSF) is a highly contagious swine disease found worldwide that has caused devastating economic losses. However, there are few efficacious mAbs against the CSF virus (CSFV) that can be used for treatment because most mAbs against CSFV are derived from mouse hybridoma cells and these murine mAbs have disadvantages of inefficient effector functions elicitations and high immunogenicity in vivo. Accordingly, we characterized whole-porcine anti-CSFV neutralizing mAbs (NAbs) isolated directly from single B cells sorted from a CSFV-vaccinated pig using the fluoresceinated conserved linear neutralizing epitope of the CSFV E2 protein and fluorophore conjugated goat anti-pig IgG. Immunoglobulin (Ig) genes were isolated via nested PCR, and two porcine mAbs termed HK24 and HK44 were produced. We determined that these mAbs can bind to E2 protein and recognize sites within this major antigenic epitope. In addition, we found that mAbs HK24 and HK44 exhibit potent neutralizing activity against CSFV, and they can protect PK-15 cells from infections in vitro with potent IC50 values of 9.3 g/ml and 0.62 g/ml, respectively. Notably, we demonstrated that these two mAbs can be used as novel reagents for detecting virus infection. These data suggest that our results not only provide a method for efficiently obtaining mAbs against CSFV but also offer promising mAb candidates for development of antibody-based diagnostic and antiviral agents.\n\nImportanceNeutralizing monoclonal antibodies (NAbs) can prevent and may slow the spread of virus infection. The discovery of NAbs that recognize classical swine fever virus (CSFV) necessitates new technologies because the NAbs produced by immunization and hybridoma technology could not be transferred to in vivo research. Multiple full-length human therapeutic antibodies have been produced via single-cell polymerase chain reactions but whole-porcine NAbs for CSFV have not been generated. In this study, two whole-porcine mAbs, named HK24 and HK44, were isolated from epitope-specific single B cells. We demonstrate that these two mAbs have potent neutralizing activity against CSFV and can protect cells against viral infection. Therefore, they may facilitate the development of vaccines or antiviral drugs that offer the advantages of stability and low immunogenicity.

molecular biology↗