Search Results (502)

Background: Trait convergence or parallelism is widely seen across the animal and plant kingdoms. For example, the evolution of eyes in cephalopods and vertebrate lineages, wings in bats and insects, or shark and dolphin body shapes are examples of convergent evolution. Such traits develop as a function of environmental pressures or opportunities that lead to similar outcomes despite the independent origins of underlying tissues, cells, and gene transcriptional patterns. Our current understanding of the molecular processes underlying these phenomena is gene-centric and focuses on how convergence involves the recruitment of novel genes, the recombination of gene products, and the duplication and divergence of genetic substrates. Scope: Despite the independent origins of a given trait, these model organisms still possess some form of epigenetic processes conserved in eukaryotes that mediate gene-by-environment interactions. These traits evolve under similar environmental pressures, so attention should be given to plastic molecular processes that shape gene function along these evolutionary paths. Key Mechanisms: Here, we propose that epigenetic processes such as histone-modifying machinery are essential in mediating the dialog between environment and gene function, leading to trait convergence across disparate lineages. We propose that epigenetic modifications not only mediate gene-by-environment interactions but also bias the distribution of de novo mutations and recombination, thereby channeling evolutionary trajectories toward convergence. An inclusive view of the epigenetic landscape may provide a parsimonious understanding of trait evolution. Full article

Background/Objectives: Molnupiravir (MOV) and nirmatrelvir (NMV) are antiviral drugs that were FDA-approved under the emergency use authorization (EUA) for coronavirus disease-2019 (COVID-19) treatment. MOV and NMV target the viral RNA-dependent RNA polymerase and main protease, respectively. Paxlovid is a combination of NMV and ritonavir (RTV), an inhibitor of the human cytochrome P450-3A4 (hCYP3A4). In this study, the structural consequences in the hCYP3A4 caused by MOV-induced mutations (MIM) were evaluated using in silico tools. Methods: MOV-induced mutations (MIM) were inserted into all the possible hotspots in the active site region of the hCYP3A4 gene, and mutant protein models were built. Structural changes in the heme-porphyrin ring of hCYP3A4 were analyzed in the presence and absence of substrates/inhibitors, including RTV. Molecular dynamics (MD) simulations were performed to analyze the effect of MIM-induced structural changes in hCYP3A4 on drug binding. Results: MD simulations confirm that MIMs, R375G and R440G in hCYP3A4 severely affect the heme-porphyrin ring stability by causing a tilt that in turn affects RTV binding, suggesting a possible inefficiency in the function of hCYP3A4. Similar results were seen for amlodipine, atorvastatin, sildenafil and warfarin, which are substrates of hCYP3A4. Conclusions: The current in silico studies indicate that hCYP3A4 containing MIMs can create complications in the treatment of COVID-19 patients, particularly with co-morbidities due to its functional inefficiency. Hence, clinicians must be vigilant when using MOV in combination with other drugs. Further in vitro studies focused on hCYP3A4 containing MIMs are currently in progress to support our current in silico findings. Full article

Grapes (Vitis spp.) are a globally significant fruit crop with a long history of cultivation and substantial cultivar diversity. Their high genetic differentiation and complex evolutionary history make them a valuable system for studying plant evolution. The chloroplast genome, known for its structural conservation and uniparental inheritance, offers a reliable molecular marker for phylogenetic reconstruction. In this study, we sequenced and assembled the complete chloroplast genomes of nine representative grape cultivars, analyzed their phylogenetic relationships, and compared structural variations. All chloroplast genomes displayed a typical quadripartite structure, with high conservation in genomic architecture, gene order and content, codon usage, and simple sequence repeats (SSRs). However, additional sequence comparisons revealed seven regions with high variation, including the genes rbcL and ndhF, and the intergenic regions rps16-trnQ, ndhC-trnV, accD-psaI, ndhF-rpl32, and trnL-ccsA. At the same time, seven natural variation sites were identified in the amino acid sequences of rbcL and ndhF. Additionally, the study’s maximum likelihood (ML) phylogenetic trees and photosynthetic index measurements suggest that developmental characteristics of grape photosynthesis may be related to the evolutionary origins of different populations. This phylogenetic classification not only elucidates the evolutionary origins of these germplasm resources but also provides a foundation for molecular-assisted breeding by identifying distinct genetic groups. Full article

Brassica juncea var. multiceps (Xuelihong), a variety of B. juncea (L.) Czern., holds considerable nutritional and economic value. However, its complete chloroplast genome and the evolutionary relationships within Brassicaceae remain poorly characterized. Using Illumina NovaSeq 6000 high-throughput sequencing, we assembled and annotated the full chloroplast genome sequence of B. juncea var. multiceps. The genome is 153,483 bp in length, with 36.36% GC content, and encodes 132 genes. Codon usage analysis identified leucine (Leu) as the dominant amino acid. Thirty-one codons had relative synonymous codon usage (RSCU; a metric for codon preference) values greater than one, with 93.55% of these preferred codons ending in A/U. We detected 37 dispersed repeats (14 forward, 18 palindromic, 3 reverse, and 2 complementary) and 315 simple sequence repeats (SSRs), with mononucleotide SSRs dominating (72.70%). Analysis of the Ka/Ks ratio, a measure of selection pressure (where values greater than one indicate positive selection), indicated that ycf1, ycf2, and nadhF genes may have undergone positive selection. The nucleotide diversity analysis revealed five hypervariable hotspot-genomic regions with high mutation rates, which are critical for phylogenetic studies. Phylogenetic analysis of 26 Brassicaceae species revealed that B. juncea var. multiceps is closely related to B. juncea. Notably, this is the first complete chloroplast genome of B. juncea var. multiceps, with unique hypervariable regions not reported in other B. juncea varieties. These findings clarify evolutionary relationships in Brassicaceae, provide molecular markers for the genetic breeding of B. juncea var. multiceps, and enhance our understanding of chloroplast genome adaptation in Brassica. Full article

Background: Lymphatic malformations (LM) are rare congenital vascular anomalies caused by abnormal development and growth of lymphatic vessels. These malformations can lead to a wide range of symptoms, from mild swelling to more severe complications. Treatment options remain limited, especially for complex cases. Recent research has suggested that PIK3CA mutations play a key role in the pathogenesis of LM, potentially offering new possibilities for targeted treatment strategies. Methods: In this study, a cohort of 36 patients diagnosed with LM, Klippel-Trenaunay syndrome (KTS), and Proteus syndrome was analyzed. PIK3CA mutations were assessed in tissue samples obtained from the LM during clinically indicated procedures using digital droplet polymerase chain reaction (ddPCR), targeting five hotspots. Results: PIK3CA mutations were found in 18 patients (50%). The most frequent mutation was p.E542K (c.1624G>A), found in 19.44% of patients, followed by p.H1047R (c.3149A>G), p.E545K (c.1633G>A), and p.H1047L (c.3140A>T) each occurring in 11.11% of the cases. Mutations were more common in isolated LMs, with 63.16% of patients exhibiting PIK3CA mutations. Conclusions: PIK3CA mutations are common in LM, supporting the potential for targeted therapies like PI3K inhibitors in treating complex cases. This research highlights the importance of genetic analysis in the management of LM and offers a new therapeutic approach. Full article

Background/Objectives: Short inverted repeats (SIRs) are abundant DNA motifs capable of forming secondary structures, such as hairpins and cruciforms, that can induce genome instability. However, their mutational consequences in cancer, particularly in osteosarcoma (OS), remain largely unexplored. Methods: In this study, we systematically identified over 5.2 million SIRs in the human genome and analyzed their mutational patterns across six common cancer types. Results: We found that increased small insertion and deletion (INDEL) density within SIR spacer regions represents a consistent feature across cancers, whereas elevated single nucleotide variant (SNV) and structural breakpoint density is cancer-type specific. Integrating whole-genome sequencing data from 13 OS patients, we found that both SNVs and INDELs are significantly enriched within SIR spacer regions in OS. Notably, genomic regions with higher SIR density tend to accumulate more somatic mutations, suggesting a link between SIR abundance and local genome instability. SIR-associated mutations frequently occur in oncogenes and tumor suppressor genes, including TP53, NFATC2, MECOM, LRP1B, RB1, CNTNAP2, and PTPRD, as well as in long non-coding RNAs. Mutational signature analysis further suggests that defective DNA mismatch repair and homologous recombination may act in concert with SIR-induced DNA structural instability to drive OS development. Conclusions: Our findings highlight SIRs as mutational hotspots and potential drivers of osteosarcoma pathogenesis. Full article

Neuroblastoma (NB) is an aggressive childhood cancer requiring intensive multimodal therapies in high-risk (HRNB) patients. Currently, invasive surgical biopsies are required to classify NB risk group and assign treatment based on the tumour genetic profile. Circulating tumour DNA (ctDNA) obtained from blood samples can be used to identify tumour biomarkers. Here we applied targeted next-generation sequencing (tNGS) using a panel of 42 genes to analyse 32 NB ctDNA samples for the presence of single-nucleotide variants and copy number changes from 28 patients in all NB risk groups. In two additional ctDNA samples, droplet digital PCR was used to detect hotspot ALK variants. Pathogenic mutations with a variant allele frequency (VAF) > 1% were identified in 13/32 (41%) ctDNA samples. ALK and PTPN11 were the most frequent, each being detected in 4/32 (13%) samples, together with oncogene amplifications. Targeted NGS of ctDNA detected actionable variants, including those absent in the diagnostic primary tumour due to spatial and temporal heterogeneity. Our findings confirm the usefulness of ctDNA in detecting genetic abnormalities in NB. Full article

Precision oncology is witnessing an increasing number of molecular targets fueled by the continuous improvement of cancer genomics and drug development. Tumor genomic profiling is nowadays (August 2025) part of routine cancer patient care, guiding therapeutic decisions day by day. Nevertheless, implementing and distilling the increasing number of potential gene targets and possible precision drugs into therapeutically relevant actions is a challenge. The availability of prescreening programs for clinical trials has expanded the description of the genomic landscape of gastrointestinal tumors. The selection of the genomic test to use in each clinical situation, the correct interpretation of the results, and ensuring clinically meaningful implications in the context of diverse geographical drug accessibility, economic cost, and access to clinical trials are daily challenges of personalized medicine. In this context, well-established negative predictive biomarkers, such as extended RAS extended mutations for anti-EGFR therapy in colorectal cancer, and positive predictive biomarkers, such as MSI status, BRAF p.V600E hotspot mutation, ERBB2 amplification, or even NTRK1, NTRK2, NTRK3, RET, and NRG1 fusions across gastrointestinal cancers, are mandatory to provide tailored clinical care, improve patient selection for treatment and clinical trials, maximize therapeutic benefit, and minimize unnecessary toxicity. In this review, we provide an updated overview of actionable genomic alterations in GI cancers and discuss their implications for clinical decision making. Full article

Medium-Chain Acyl-CoA Dehydrogenase Deficiency (MCADD) is a metabolic disorder caused by mutations in the ACADM gene, leading to impaired fatty acid oxidation. The present study aims to analyze the prevalence and genetic mutation characteristics of MCADD among newborns in Hefei, China, providing insights for the diagnosis, treatment, and prevention of MCADD. A retrospective analysis was conducted on data from newborns diagnosed with MCADD at the Hefei Newborn Disease Screening Center between January 2016 and December 2024. Screening was performed using tandem mass spectrometry (MS/MS), complemented by next-generation sequencing (NGS) for genetic testing. Out of 880,224 screened newborns, 16 cases of MCADD were diagnosed, resulting in a prevalence of 1 in 55,014. A total of 31 mutation sites in the ACADM gene were identified, with 18 different mutation types. The hotspot mutations were c.449-452del (p.T150Rfs*4) and c.1085G>A (p.G362E), each with a mutation frequency of 16.13% (5 out of 31). Additionally, three novel mutations were identified: c.468+5G>A, c.854C>G, and c.428_431delinsTCTTCTTTTGTT. Following diagnosis, patients received health education, dietary guidance, and symptomatic treatment, all resulting in favorable prognoses without any acute metabolic decompensation events. The prevalence of MCADD is lower in Asia compared to Europe and America. The hotspot mutations for MCADD in Hefei are c.449-452del and c.1085G>A. Diagnosis should integrate results from both octanoylcarnitine (C8) levels and genetic testing. Early screening, diagnosis, treatment, and scientific prevention strategies are essential for reducing adverse outcomes in children with MCADD. Full article

The tumour suppressor protein p53 plays a central role in safeguarding genomic integrity through the regulation of DNA repair, cell cycle arrest, and apoptosis. Mutations in TP53, particularly within its DNA-binding domain, are among the most frequent genetic alterations in human cancers and are strongly associated with chemoresistance and poor prognosis. In this study, all TP53 mutations reported in the COSMIC database were systematically mapped onto all experimentally resolved TP53 three-dimensional structures available in the Protein Data Bank, supplemented with AlphaFold-predicted models to achieve full structural coverage. Mutations were classified according to their structural context—protein core, interface regions, ligand- and zinc-binding sites, and intrinsically disordered regions—and evaluated using complementary sequence- and structure-based predictive tools. The analysis revealed distinct mutational hotspots, differential distribution across structural regions, and context-dependent effects on stability and DNA-binding capacity. Notably, a subset of mutations exhibited consistent predictions of high destabilisation across all structural contexts, underscoring their potential as drivers of functional inactivation. By providing a comprehensive structural map of TP53 alterations, this work offers a valuable resource for understanding mutation-specific mechanisms of p53 dysfunction and for guiding the development of precision therapeutic strategies aimed at restoring its tumour-suppressive functions. Full article

Helicobacter pylori (Hp), a Class I carcinogen infecting over 50% of the global population, is increasingly resistant to conventional antibiotics. This study presents an AI-engineered probiotic strategy targeting urease, a key Hp virulence factor. A humanized single-domain antibody (UreBAb), previously identified and selected in our laboratory, was synthesized commercially and modeled using AlphaFold2, with structural validation conducted via SAVES 6.0. Molecular docking (PyMOL/ClusPro2) and binding energy analysis (InterProSurf) identified critical urease-active residues: K40, P41, K43, E82, F84, T86, K104, I107, K108, and R109. Machine learning-guided optimization using mCSA-AB, I-Mutant, and FoldX prioritized four mutational hotspots (K43, E82, I107, R109), leading to the generation of nine antibody variants. Among them, the I107W mutant exhibited the highest activity, achieving 65.6% urease inhibition—a 24.95% improvement over the wild-type antibody (p < 0.001). Engineered Escherichia coli Nissle 1917 (EcN) expressing the I107W antibody significantly reduced gastric HP colonization by 4.42 log10 CFU in the treatment group and 3.30 log10 CFU in the prevention group (p < 0.001 and p < 0.05, respectively), while also suppressing pro-inflammatory cytokine levels. Histopathological (H&E) analysis confirmed that the I107W antibody group showed significantly enhanced mucosal repair compared to wild-type probiotic-treated mice. Notably, 16S rRNA sequencing revealed that intestinal microbiota diversity and the abundance of core microbial species remained stable across different ethnic backgrounds. By integrating AI-guided antibody engineering with targeted probiotic delivery, this platform provides a transformative and microbiota-friendly strategy to combat antibiotic-resistant Hp infections. Full article

We previously developed SA-conf, a method designed to quantify backbone structural variability in protein targets. This approach is based on the HMM-SA structural alphabet, which enables efficient and rapid comparison of local backbone conformations across multiple structures of a given target. In this study, SA-conf (version for python2.7) was applied to a dataset of 130 crystallographic chains of Bcl-xL, a protein involved in promoting cell survival. SA-conf quantified and mapped backbone structural variability, revealing the protein’s capacity for conformational rearrangement. Our results showed that while most mutations had minimal impact on backbone conformation, some were associated with long-range structural effects. By jointly analyzing residue flexibility and backbone rearrangements across apo and holo structures, SA-conf identified key regions where the backbone undergoes structural adjustments upon ligand binding. Notably, the $\alpha 2$–$\alpha 3$ region was shown to be a hotspot of structural plasticity, exhibiting ligand-specific conformational signatures. Furthermore, SA-conf enabled the construction of a structural map of the binding site, distinguishing a conserved anchoring core from flexible peripheral regions that contribute to ligand specificity. Overall, this study highlights SA-conf’s capacity to detect conformational changes in protein backbones upon ligand binding and to uncover structural determinants of selective ligand recognition. Full article

While omega-6 fatty acids play an important role in normal cell function, their excess in the diet is associated with an increased risk of developing diseases such as obesity, non-alcoholic fatty liver disease (NAFLD), inflammatory bowel disease (IBD) and Alzheimer’s disease. Furthermore, excessive intake has been shown to lead to chronic inflammation, which is related to increased production of reactive oxygen species (ROS). This conditioncan initiate lipid peroxidation in cell membranes, leading to the degradation of their fatty acids. One of the main products of omega-6 peroxidation is the α,β-unsaturated aldehyde, i.e., 4-hydroxynonenal (4-HNE), which is able to form four diastereoisomeric adducts with guanine. These 4-HNE adducts have been identified in the DNA of humans and rodents. Depending on their stereochemistry, they are able to influence double helix stability and cause DNA–DNA or DNA–Protein cross-links. Moreover, studies have shown that 4-HNE adducts formed in the human genome are considered mutation hotspots in hepatocellular carcinoma. Although the cell possesses defence mechanisms, without a well-balanced diet allowing correct cell function, they may not be sufficient to protect the genetic code. This review provides an overview of the molecular mechanisms underlying oxidative stress, lipid peroxidation, and the formation of DNA adducts. Particular emphasis is placed on the role of an omega-6-rich diet in inflammatory diseases, and on the formation of 4-HNE, which is a major product of lipid peroxidation, and its broader implications for genome stability, ageing, and disease progression. Full article

Repetitive DNA sequences are abundant in genomes and can adopt alternative DNA structures (i.e., non-B DNA). One such structure, Z-DNA, has been shown to stimulate genetic instability in a variety of organisms, including human cells and mice. Z-DNA-forming sequences are enriched at mutation hotspots in human cancer genomes, implicating them in cancer etiology. Aging is a known risk factor for the development of cancer, and genetic instability is a hallmark of both aging and cancer. However, how aging affects the mutagenic potential of Z-DNA has not yet been investigated. Here, we explored the effects of aging on the mutagenic processing of Z-DNA using a transgenic mouse model. Surprisingly, Z-DNA-induced mutations decreased or remained unchanged with increasing age. Cleavage of Z-DNA was unaffected with increasing age, suggesting that downstream repair processing, such as double-strand break repair processes, may be involved in the age-related changes in Z-DNA-induced mutagenesis in mice. Full article

Plastic pollution is a growing global challenge, and traditional plastic waste management methods are proving inadequate in tackling the issue. Enzymatic biodegradation has emerged as a promising alternative or addition to plastic waste management due to its environmentally friendly profile. Polyethylene terephthalate (PET) is among the most widely used polymers in packaging, and recent research has identified several PET-degrading enzymes, such as TfCut2, IsPETase, and LCC, as promising candidates for biodegradation applications at the industrial level. This has led to extensive efforts to improve their catalytic efficiency, with targeted mutagenesis being the preferred method employed for their modification. To this end, molecular dynamics (MD) simulations coupled with experimental validation have provided critical atomistic-level insights into the effect of mutations on enzymatic function. The present systematic review examines the role of mutations in determining enzymatic activity and thermostability, analyzing their structural and mechanistic contributions across 20 studies. The integration of MD simulations and experimental findings allows elucidation of the mechanistic details governing polymer degradation, as well as identification of key residue and enzyme hotspots that enhance catalytic performance. The review further highlights the role of MD simulations as powerful tools in providing valuable insights to guide targeted mutations for enzyme efficiency optimization. Full article