Search Results (334)

Autoantigens, targets of B cell antibodies, account for ~10% of the human proteome. It is not well understood why or how particular self-proteins become autoantigens. Prominent theories posit that failures of the immune system at various levels or exposure of aberrant proteins to the immune system are responsible for autoantigenicity. In contrast, we propose a completely unrelated mechanism of autoantigenicity that is based on normal cell functioning. We suggest that, when a protein associates with one of the ~100 types of biomolecular condensates, protein–protein interaction therein causes changes in protein structure or conformation that signal an untolerized state to the immune system. This proposal is derived from the fact that many macromolecules are more concentrated within condensates than in the extra-condensate environment. Thus, the propensity for macromolecular interaction may be greater in condensates compared with the non-condensate environment. In support of this proposal, we present examples of predicted conformational differences, with and without accompanying secondary structure differences, between proteins in known condensate heteromeric complexes and in their free monomer forms. In each case, the differences correlated with predicted B-cell binding, supporting our model. Further, from a compilation of ~1900 autoantigens, we estimate that autoantigens are twice as prevalent in condensates compared with the entire human proteome (Chi squared p < 0.0001), further suggesting that a property of condensates, e.g., protein conformational change, may contribute to autoantigenicity. Full article

Equine infectious anemia virus (EIAV), with the simplest lentiviral genome, is a key model for studying fundamental lentiviral biology. Infectious viral particles are produced only when the Gag protein selectively encapsidates full-length genomic RNA via the packaging signal (Psi), yet the structural and functional features of EIAV Psi remain poorly characterized. Using computational prediction and dimethyl sulfate probing, we identified four stem-loops (SLs) within a ~120 nt region in the 5′ leader of the genome, spanning from downstream of the primer binding site through 20 nt into the gag coding sequence. In vitro dimerization assays demonstrated that a palindromic sequence (5′-CUGGCCAG-3′) within SL3 acts as a critical determinant of RNA dimerization. Functional screening using both an EIAV pseudovirus packaging system and the infectious clone EIAVuk revealed that deletion or mutation of the stem-loops significantly impairs viral packaging and replication, with SL2 deletion or its stem disruption causing the most severe defects. RNA-seq analysis of RNAs bound by wild-type Gag versus a zinc-finger mutant (H391K/H410K) identified two candidate Gag-associated sites: the SL2 stem and the SL2-SL3 junction. Targeting these regions with phosphorothioate-modified antisense oligonucleotides potently inhibited pseudovirus production and the replication of infectious EIAVuk. Our findings defined the secondary structure and functional organization of the EIAV core packaging region and established the SL2 stem and SL2-SL3 junction as candidate packaging determinants and promising targets for RNA-based antiviral intervention. Full article

Medium-resolution cryo-electron microscopy (cryo-EM) density maps preserve substantial information about protein secondary-structure organization; however, accurately recovering the topology and connectivity of α-helices and β-strands remains challenging due to noise, structural heterogeneity, and the intrinsic resolution limitations that obscure residue-level detail. Topology determination is a key intermediate step toward building atomic protein models from medium-resolution cryo-EM density maps. It requires identifying the correct correspondence and orientation between secondary-structure elements (SSEs), i.e., α-helices and β-strands, predicted from the amino-acid sequence and those detected in the three dimensional (3D) density map. Despite significant advances in cryo-EM reconstruction and molecular modelling, this correspondence problem remains a challenging task, particularly in the presence of noisy density maps and in large, topologically complex α/β proteins. To address this issue, we propose a fully automated, classification-based framework that infers protein secondary-structure topology directly from medium-resolution cryo-EM density maps. Specifically, we cast topology determination as a supervised classification problem in three-dimensional space, leveraging geometric learning on model-derived Cα coordinate representations to establish SSE correspondences, and a Dynamic Time Warping (DTW)-based procedure to resolve density-stick directionality. Validation on a benchmark of 38 proteins spanning both simulated and experimental cryo-EM maps and covering diverse fold classes (α, β, and α/β) demonstrates strong and consistent performance. Among the evaluated predictors, the Voronoi (1-NN) classifier achieves the highest average correspondence quality, with a mean F1-score of 96.82% across the full benchmark. The framework also scales to large, topologically dense targets containing up to 65 secondary-structure elements while preserving very fast correspondence inference (<3 ms), offering a substantial improvement over prior baselines in both accuracy and computational cost. Overall, the classification-driven strategy provides reliable SSE-to-density matching and, when coupled with DTW-based direction selection, yields stronger topology constraints that directly support model building and refinement from medium-resolution cryo-EM reconstructions, while remaining easy to integrate into existing structural interpretation pipelines. Full article

Background: Long non-coding RNAs (lncRNAs) are increasingly recognized as key regulators of gene expression, playing pivotal roles in diverse biological processes, including reproduction. This study identified and characterized lncRNAs located near fertility-associated genes in Retinta beef cattle, exploring their potential regulatory roles via DNA–RNA triplex formation using in silico approaches. Methods: We applied an integrative bioinformatics pipeline to identify potential triplex interactions, predicting structurally accessible regions within the lncRNAs and demonstrating the statistical enrichment of binding sites across known regulatory genomic elements. Results: Twelve protein-coding genes previously linked to female fertility or male scrotal circumference were analyzed, revealing 16 unique lncRNAs within ±50 kb windows, predominantly on BTA5. We predicted high-confidence triplex-forming oligonucleotides (TFOs) for most gene-lncRNA pairs. Our results suggest robustness and sequence specificity, as interactions were disrupted by sequence permutation or when a control background sequence was used. RNA secondary-structure analysis revealed that TFOs generally lie in exposed regions, supporting their accessibility for triplex formation. Furthermore, promoter and regulatory regions of fertility-associated genes were enriched in predicted triplex target sites (TTSs), with some overlapping CpG islands and enhancer regions, leading to the hypothesis that these lncRNAs might play a role in epigenetic regulation. Conclusions: Overall, these findings establish computationally derived hypotheses regarding the potential molecular mechanisms by which lncRNAs may modulate reproductive efficiency in cattle and highlight specific lncRNAs as promising targets for functional studies and marker-assisted breeding. Full article

This study aimed to characterize the draft genome of Arthrospira platensis NH isolated in Vietnam and evaluate its phylogenetic position within cyanobacteria. Phylogenetic analysis based on 16S rRNA gene sequences confirmed that A. platensis NH belongs to the Arthrospira clade. The assembled genome comprises 5,548,511 bp and contains 4728 genes, including 4683 protein-coding sequences, 42 tRNA genes, and 3 rRNA genes. Genome mapping revealed conserved gene organization with an overall GC content of 44.45%. A comparative genomic analysis with other Arthrospira strains (A. platensis NIES-39 and C1) demonstrated high sequence conservation, supporting their close genetic relationships. Secondary structure prediction showed that all 42 tRNA types adopt typical cloverleaf structures, while the ribosomal RNA genes (16S, 23S, and 5S rRNA) exhibit conserved base composition. An analysis of 16S rRNA sequences from 13 cyanobacterial taxa identified 230 polymorphic sites, providing informative markers for phylogenetic divergence among genera. Collectively, these results establish a comprehensive genomic and phylogenetic framework for A. platensis NH and provide insights into its genetic relationships and potential biotechnological applications. Full article

We performed a protein-docking study for eight DNA aptamers (SEQ1–SEQ8) against chicken Cluster of Differentiation 40 (chCD40), which were experimentally identified via SELEX in our previous study. In silico and molecular docking analyses were performed to predict and obtain the secondary and tertiary structures of the aptamers. Aptamers SEQ3 and SEQ4, which showed the best inhibitory effects, were selected and utilized to produce a DNA-based vaccine adjuvant using rolling circle amplification (RCA). These aptamers had been previously characterized via mass spectroscopy to determine their molecular weight and regions that could potentially interact with chCD40. In the present study, these results were corroborated and expanded. A series of free software methods, including Mfold v.1.0, 3dADN v.2.0, ClusPro v.2.0, Hdock v.1.0, and PLIP v.1.0, were used to determine the aptamers’ secondary and tertiary structures and docking interactions, as well as the specific residues involved in the interactions and their distances. The structures were used to explain and thus understand their effect on the binding, selectivity, and stability of the aptamers. The main objective of the study was to determine whether these aptamers could be used as vaccine adjuvants against viral and bacterial pathogens, specifically chicken avian influenza. The docking results were in good agreement with the experimental and biological results. The procedure employed in this study could be an easy and effective tool for exploring the potential of the new technology of systematic evolution of ligands by exponential enrichment (SELEX) in the preparation of aptamers to control viral and bacterial infections as well as diseases, such as cancer and Alzheimer’s. Full article

Estimation of the postmortem interval (PMI) remains a major challenge in forensic science. We used attenuated total reflection (ATR)–Fourier-transform infrared (FTIR) spectroscopy combined with chemometric modeling for PMI prediction using vitreous humor samples from 20 forensic cases with known PMI (24.8–97.6 h) and 10 with unknown PMI. The intensities of vibrational bands commonly associated with PMI were analyzed, and several peaks in the carbohydrate/phosphate region showed significant correlations with PMI. Principal component analysis revealed time-dependent spectral evolution, with PC1 (48.1%) associated mainly with carbohydrate/phosphate variations and PC2 (37.6%) with protein structural changes. Partial least squares regression with two latent variables achieved a cross-validated RMSE of 15.8 h (R² = 0.53) on all 20 known samples. Variable importance analysis identified glycoprotein degradation (1190 cm⁻¹) and phospholipid breakdown (736 cm⁻¹) as the dominant predictors, with traditional carbohydrate bands playing a secondary role. Predictions for unknown samples ranged from 27.1 to 80.1 h, with five of ten falling within the 90% prediction interval (±20 h) of the available estimates. This study presents a promising PMI estimation model that performed well on unseen samples, even if the sample size represents a methodological limitation that will be addressed in future investigations through larger, more diverse datasets. Full article

Background: Protein phosphatase 2Cs (PP2Cs) constitutes the largest phosphatase family in plants, playing a pivotal role in signal transduction. Within this family, the PP2C.D subfamily exerts significant influence on cell elongation and stress adaptation by mediating the ‘SAUR-PP2C.D-H+-ATPase’ regulatory module in the auxin signaling pathway. In rice, OsPP2C61 is a PP2C member whose molecular features and potential regulatory context remain unclear. Methods: Our study conducted a preliminary characterization of OsPP2C61 through integrated bioinformatics analysis, spatiotemporal expression profiling, and subcellular localization experiments in tobacco leaf cell. Results: OsPP2C61 encodes a 377-amino-acid protein predicted to be hydrophilic, basic, and structurally unstable. Secondary-structure prediction identified three major elements with random coils as the predominant component, whereas 3D modeling indicated alternating α-helices and β-sheets consistent with a canonical PP2C fold. Phylogenetic inference placed OsPP2C61 within the PP2C.D clade and revealed conserved motifs shared with OsPP2C25, OsPP2C28, and OsPP2C39. Promoter analysis showed enrichment of abscisic acid (ABA)- and methyl jasmonate (MeJA)-responsive elements along with multiple stress-related cis-regulatory motifs. Spatiotemporal expression analysis showed that OsPP2C61 is highly expressed in roots. Subcellular localization assays further demonstrated that the OsPP2C61-GFP fusion protein localizes to the nucleus and the plasma membrane when transiently expressed in epidermal cells of Nicotiana benthamiana. Conclusions: This work delivers the first comprehensive characterization of OsPP2C61, establishing a foundation for mechanistic studies and positioning OsPP2C61 as a candidate gene for rice improvement. Full article

Quantitative structure–activity/property relationship (QSAR/QSPR) is a well-established methodology widely used to model molecular properties based on structure and is applied in fields such as drug design and environmental protection. The knowledge and procedures developed and used in QSPR modelling will be applied to the validation of protein folding rate models. Understanding the protein folding process is considered one of the most important scientific topics, and identifying the fundamental factors responsible for protein folding has been the subject of intensive research over the past 30 years. Among the structural descriptors determining the protein folding rate, the length of the protein sequence, the content of regular secondary structures, and the average contact row distance between amino acids in the 3D structure are the most important. Comparative studies of different methods for predicting protein folding rates are occasionally published, and we conducted one such study. We found that the experimental data in literature databases and the data available online are inconsistent and scattered. This is partly due to differences in experimental data and protein sequence lengths, but more so due to the questionable quality of the models themselves. We observed very large deviations in the predictions of ln(k_f) by some of the analysed models implemented as web servers. The root mean square errors (RMSEs) of some of the analysed models in predicting ln(k_f) for a new external set of proteins are much larger than the RMSEs obtained for the same models on the training sets. External validation demonstrates that protein folding rate models available on web servers have accuracy for external protein sets comparable to that of a simple model based solely on the logarithm of protein chain length. This finding, which highlights the importance of external model validation as recommended by the OECD guidelines for QSAR validation, is fundamental and offers a new perspective for improving protein folding rate models by applying the knowledge and procedures used in the QSPR methodology. Full article

Nigrospora musae ST1 is a newly identified pathogen responsible for leaf spot disease in Idesia polycarpa. In order to further advance our understanding of this strain and improve management strategies for the leaf spot disease, the PacBio Sequel II platform was used to perform whole-genome sequencing of N. musae ST1. The assembled genome comprised 42 contigs, with a total length of 49,259,803 bp and an average GC content of 56.23%. Functional annotation identified 12,063 protein-coding genes, including 125 Transporter Classification Database (TCDB)-related genes, 3600 pathogen host interaction (PHI) genes, 2503 Virulence Factor Database (DFVF)-related genes, and 722 genes encoding carbohydrate-active enzymes (CAZymes). Integrated analyses of the secretome, PHI, and DFVF databases revealed six secreted carbohydrate-active enzymes implicated in plant pathogenicity, including three glycoside hydrolases, two pectinate lyases, and one cutinase, potentially playing important roles in pathogenicity. A total of 77 secondary metabolite gene clusters were predicted. Comparative genomic analysis between N. musae ST1 and other Nigrospora species revealed differences in genome rearrangements in Nigrospora fungi. In conclusion, this study has clarified the whole-genome structural characteristics and evolutionary relationships of the newly reported pathogenic fungus, N. musae ST1. It provides a theoretical foundation for future investigations into the pathogenic mechanisms of N. musae ST1 infection in I. polycarpa, as well as potential targets for disease control. Full article

Enhancer of Zeste Homolog 2 (EZH2), the catalytic subunit of Polycomb Repressive Complex 2 (PRC2), mediates histone H3 lysine 27 trimethylation (H3K27me3), an epigenetic modification associated with transcriptional repression. EZH2 inhibitors (EZH2is) gained attention after the first-in-class drug Tazemetostat received FDA approval for treating epithelioid sarcoma. Preclinical studies suggest that EZH2is could be effective against melanoma, but their general inability to cross the blood–brain barrier (BBB), among others, limits the treatment of secondary brain metastases. Based on these limitations, we designed SG-8, a novel compound derived from TDI-6118 (a known brain-penetrant EZH2i). In silico docking predicted that SG-8 may exhibit high affinity for EZH2 as well as for another PRC2 subunit, Embryonic Ectoderm Development (EED). In addition, in vitro PAMPA assays suggested passive BBB permeability of SG-8. In cell-based assays, SG-8 and the structurally related EZH2i PF-06726304 displayed lower cytotoxicity than Tazemetostat in both primary (A375) and metastatic (Colo-679) human melanoma cells. Western blot analysis showed that SG-8 and PF-06726304 markedly reduced EED protein levels and, to a lesser extent, EZH2 levels, without affecting total H3K27me3, consistent with preserved canonical PRC2 activity. Instead, treatment with both compounds—most prominently SG-8—was associated with reduced phosphorylation levels of EZH2 (Ser21) and its upstream regulator Akt (Ser473), suggesting that modulation of the Akt–EZH2 signaling axis may at least partially contribute to their anti-melanoma activity. Full article

Accumulating studies have identified the pivotal role of long non-coding RNAs (lncRNAs) in participating in host–virus interactions during virus infections. However, the regulatory roles of lncRNAs in influenza A virus (IAV) infection are still not fully elucidated. In this study, using high-throughput sequencing, we comprehensively compared the expression profiles of lncRNAs and mRNAs in mouse lungs infected either with the nonpathogenic parental (SDL124) H7N9 virus or its moderately pathogenic mouse-adapted (S8) variant. A total of 7636 significantly differentially expressed (SDE) lncRNAs were obtained in the S8-infected group compared to the mock group. As for the SDL124 group, 1042 SDE lncRNAs were identified. Subsequently, the mRNAs co-expressed with SDE lncRNAs were subjected to functional annotation and pathway enrichment analysis. The results indicated that the target mRNAs regulated by the S8 virus were mainly enriched in various immunological processes and exhibited a strong correlation with inflammatory-related signaling pathways. Moreover, 12 lncRNAs and 10 mRNAs co-expressed with SDE lncRNAs were selected and successfully verified by RT-qPCR. Among these lncRNAs, NONMMUG032982.2 and NONMMUG032328.2 exhibited strong antiviral activity against IAV. Additionally, these two lncRNAs were chosen for further in-depth bioinformatics analysis, including transcription factor prediction, coding capacity assessment, genomic location, construction of secondary structure, and prediction of potential interacting proteins. Taken together, these findings provide a cluster of lncRNAs probably associated with the virulence of IAV in mice and shed light on the anti-IAV effects of two functional lncRNAs, establishing a molecular foundation for further exploring the regulatory mechanisms of lncRNAs in IAV infection. Full article

Aspergillus flavus infection and accumulation of carcinogenic aflatoxins are detrimental to maize (Zea mays) production and consumption. We investigated lncRNA–RBP interactions during maize–A. flavus crosstalk using transcriptomic profiling, structural analysis, molecular docking simulations, and machine learning approaches. Analysis of 18 RNA-seq datasets identified 2104 lncRNAs in maize, of which 461 were differentially expressed under A. flavus infection. Distinct lncRNAs were preferentially induced under infection (e.g., Zm00001eb303170) or normal germination (e.g., Zm00001eb144150, Zm00001eb406410). RNA secondary structure predictions indicated high structural heterogeneity and thermodynamic stability, consistent with dynamic regulatory potential. Docking simulations with six key RNA binding proteins (RBPs)—including branch point bridging protein (BPB), KH domain protein, and pentatricopeptide repeat (PPR) proteins—demonstrated strong lncRNA–protein binding, with the lncRNA1–BPB complex exhibiting the highest binding affinity. ML algorithms identified the crucial role of tryptophan in determining interactions, while lncRNA17-KH and lncRNA1-BP complexes were found to have the best interaction under normal germination and A. flavus infection, respectively. The lncRNA–miRNA–mRNA regulatory network highlighted lncRNAs functioning as decoys or precursors of stress-responsive miRNAs (e.g., zma-miR156, zma-miR164, zma-miR399). These interactions targeted transcriptional regulators, splicing factors, and metabolic enzymes implicated in stress tolerance, seed germination, and systemic acquired resistance. The maize lncRNAs are active regulatory molecules embedded in complex RBP and miRNA interaction networks that fine-tune gene expression during A. flavus infection. The study provides novel insights into lncRNA-mediated resistance mechanisms and offers potential molecular targets for breeding or gene editing to mitigate aflatoxin contamination. Full article

WRKY transcription factors serve as key regulators in plants, playing important roles in growth and development, secondary metabolism, and stress responses. Here, a comprehensive genome-wide analysis identified 58 WRKY genes (LcWRKYs) in litchi for the first time. All LcWRKY proteins were predicted to be hydrophilic and localized in the nucleus. Phylogenetic analysis classified them into three major groups (Groups I, II, and III), with a pronounced expansion of Group II, which contained 42 members divided into five subgroups. Members within the same phylogenetic clade exhibited highly similar exon–intron structures and conserved motif compositions, indicating strong evolutionary conservation. LcWRKYs were unevenly distributed across the litchi chromosomes, with chromosome 3 showing the highest gene density. Collinearity analysis suggested that both segmental and tandem duplications contributed to the evolutionary expansion of this family. Notably, promoter cis-acting element analysis revealed that LcWRKYs are enriched with light-responsive, hormone-responsive (e.g., ABA, MeJA, SA), and stress-responsive elements, suggesting their potential involvement in integrating light signaling, hormonal pathways, and environmental stress responses. Integrative expression analysis further revealed that multiple LcWRKYs were significantly up-regulated during the middle and late stages of fruit development in cultivars such as ‘Feizixiao’ and ‘Nuomici’. Consistent with these patterns, qRT-PCR validation demonstrated a pronounced induction of four representative genes (LITCHI004628.m1, LITCHI018082.m1, LITCHI021964.m1, and LITCHI030932.m1) at 40 days post-anthesis, followed by gene-specific expression trajectories at later stages, indicating their potential involvement in regulating fruit development, particularly during the mid-developmental stage. Altogether, the results of this study provide insight into the expansion and potential functional diversification of WRKY transcription factors in litchi and identify candidate regulators associated with fruit development, offering valuable targets for future functional studies and genetic improvement. Full article

Panax ginseng is a traditional Chinese herbal medicine. Ginsenosides, the main bioactive components responsible for the medicinal value of ginseng, are regulated by transcription factors. Among these regulatory factors, basic leucine zipper (bZIP) transcription factors play crucial roles in plant development and secondary metabolism. To verify that members of the bZIP gene family are involved in regulating ginsenoside biosynthesis and explore their potential mechanisms of action, a correlation analysis was first conducted in this study between the expression levels of PgbZIP genes and ginsenoside content. Additionally, the effects of single-nucleotide polymorphisms (SNPs) and Insertions/Deletions (InDels) on ginsenoside content were analyzed in this study. Through these analyses, PgbZIP48-3, a gene highly associated with ginsenoside biosynthesis, was identified. Subsequently, we systematically analyzed PgbZIP48-3, including its gene structure, protein properties, and phylogenetic relationships. To further verify the function of PgbZIP48-3, an overexpression vector was constructed. Positive ginseng hairy roots were obtained via Agrobacterium-mediated transformation of explants, and the ginsenoside content in these positive hairy roots was determined. The results showed that in the PgbZIP48-3 overexpression positive lines, the contents of ginsenosides Re, Rb2, Rb3, Rc, and Rd were significantly higher than those in the control group, whereas the contents of ginsenosides Rg1, Rf, and Rb1 were lower than those in the control group. Finally, by investigating the SNP/InDel data of PgbZIP48-3 in 346 accessions of a natural P. ginseng population and constructing a predicted interaction map between PgbZIP48-3 and key enzyme genes involved in ginsenoside synthesis, this study preliminarily revealed the potential molecular mechanism by which PgbZIP48-3 regulates ginsenoside biosynthesis from two dimensions: gene mutation and gene expression correlation. Meanwhile, this study provides genetic resources for the breeding of ginseng cultivars with high ginsenoside content. Full article