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PubMed2025

Development of chloroplast transformation for five species in the genus Nicotiana.

Technologies for the stable genetic transformation of the plastid (chloroplast) genome are currently restricted to a small number of species. The development of highly efficient tissue culture, regeneration, and selection procedures represents the major hurdle that needs to be overcome to extend the species range of the transplastomic technology. Here, we report the development of efficient plastid transformation protocols for five species in the genus Nicotiana: the model species N. benthamiana, the tree tobacco N. glauca, the ornamental plants N. langsdorffii and N. longiflora, and the wild species N. otophora. We have optimized medium composition for efficient regeneration from leaf explants in all five species and determined suitable selection conditions for plastid transformation. We successfully isolated multiple transplastomic lines for each species and also generated lines that express the fluorescent reporter protein DsRed. Molecular and genetic analyses confirmed the homoplasmic state of the transplastomic lines and demonstrated maternal inheritance of the transgenes. Our work makes plastid genome engineering available for a set of new species and enables new applications in horticultural research and ecology. It also informs the future development of plastid transformation technology for other species.

Nicotiana↗

PubMed2026

Ecological Restoration of the Soil-Like Function in the Bauxite Residue: Natural Microbiomes Mediated Molecular Transformation of Dissolved Organic Matter.

Soilization of bauxite residues offers a scalable route for long-term carbon management and ecological restoration. However, the microbial processes that transform exogenous organic inputs into stable soil-like carbon pools remain poorly resolved. Here, we combined cross-ecosystem meta-analysis, machine-learning prediction, native synthetic community (SynCom) construction, 13C-labeled straw microcosms, field validation, Fourier transform ion cyclotron resonance mass spectrometry, and genome-resolved metagenomics to unravel microbiome-mediated carbon transformation at the dissolved organic matter (DOM) molecular scale. Our meta-analysis revealed that alkaline industrial wastes retained soil-like DOM signatures but were enriched in microbial humic- and protein-like components, indicating active yet incomplete carbon processing. Guided by these patterns, native SynCom inoculation increased 13C incorporation into total organic carbon (TOC) and dissolved organic carbon (DOC), enlarged biodegradable and adsorbable DOC fractions, and shifted DOM from recalcitrant aromatic pools toward oxygenated carbohydrate-, tannin-, and phenolic-like molecular classes. Genome-resolved analyses linked this transformation to complementary polymer degradation and nutrient-cycling functions across fungal and bacterial guilds, including enriched carbohydrate-active enzymes in straw-carbon-utilizing metagenome-assembled genomes. Null model and thermodynamic analyses further showed that microbial communities were constrained by homogeneous selection, whereas DOM molecules were diversified through variable selection and redox-dependent transformation. Field-scale validation confirmed that SynCom promoted TOC and DOC accumulation and humic-like, high-density DOM fractions under alkaline conditions. Together, these findings establish a mechanistic framework in which functional microbiomes couple plant carbon depolymerization, DOM molecular diversification, and mineral-interactive carbon stabilization, providing a microbiome-guided strategy for carbon sequestration and soilization in the bauxite residue.

Soil↗

PubMed2026

Impact of wheat GRF4-GIF1 morphogenic regulators on transformation and genome editing efficiency in elite barley cultivars.

INTRODUCTION: Efficient genetic transformation is essential for the delivery of the CRISPR/Cas9 genome editing system and thus represents an important technology for breeding-oriented research in barley (Hordeum vulgare L.). However, transformation and plant regeneration from tissue culture remain challenging in non-model barley genotypes. Previous studies demonstrated that expression of a chimeric fusion between two interacting transcription factors, GROWTH-REGULATING FACTOR 4 (GRF4) and GRF-INTERACTING FACTOR 1 (GIF1), enhances regeneration capacity in wheat and other species. METHODS: In this study, we evaluated the effect of the wheat-derived GRF4-GIF1 morphogenic regulators on biolistic transformation and genome editing efficiency in three commercial barley cultivars: Tselinniy 5, Aley, and G-23035. RESULTS: The JD633 construct carrying GRF4-GIF1 enabled recovery of stable transformants in all three genotypes, with efficiencies ranging from 2.5% to 5%, whereas the control construct lacking morphogenic regulators resulted in no transgenic events in any of the tested varieties. Among transformed T0 plantlets, genome editing efficiency reached 64.3%, with predominantly biallelic mutations that were stably inherited in the T1 generation. Molecular screening revealed the presence of plasmid-free edited plants in the T0 generation, likely arising from transient Cas9 expression, and provided evidence of tissue chimerism. DISCUSSION: These results demonstrate that the GRF-GIF system facilitates genome editing, providing a practical framework for accelerating precision breeding in barley.

CRISPR/Cas9↗

PubMed2026

Tissue-based genomic instability markers for predicting malignant transformation in oral leukoplakia and proliferative verrucous leukoplakia: a systematic review.

OBJECTIVES: Although several biomarkers have been described for predicting malignant transformation in oral leukoplakias (OLs) and proliferative verrucous leukoplakias (PVLs), no systematic review has comprehensively evaluated tissue-based genomic instability markers. This review aimed to evaluate the evidence for these markers and their potential role in biomarker panel development. METHODS: A systematic review across PubMed, Embase and Cochrane Library was performed to identify studies evaluating the differences in tissue-based genomic markers between OL and PVL patients with and without malignant transformation. RESULTS: 34 observational studies comprising 3,237 patients were included, and genomic aberrations were categorised into DNA-level, chromosomal, and gene-specific alterations. For studies on OLs, DNA-level and chromosomal markers for which individual studies reported associations with malignant transformation included aneuploidy, impaired DNA repair capacity, loss of heterozygosity, chromosomal instability, and copy number alterations. Multiple gene-specific alterations also showed associations (e.g., TP53, MKI67, FGFR1), but findings varied across studies. The genomic markers of PVLs differed substantially, with fewer consistent predictors found. No meta-analysis was performed as all included studies were observational. CONCLUSIONS: Genomic instability across multiple levels contributes to malignant transformation, and represents a promising biological framework for predicting malignant transformation for OLs. While no single marker reliably demonstrates sufficient predictive performance, the integration of complementary genomic alterations with clinical and histopathological risk factors may provide a basis for the development of robust multi-marker panels. Future prospective studies using standardised detection methods and multivariable prediction models are required before clinical implementation. SYSTEMATIC REVIEW REGISTRATION: identifier CRD42024585830.

carcinoma↗

PubMed2025

A genotype-independent and highly efficient Agrobacterium-mediated soybean genetic transformation system.

A stable and efficient transformation system is crucial for functional genomics and trait improvement in soybean. This study developed a tissue culture based genetic transformation system incorporating dual selection (Spectinomycin and RUBY). This system significantly enhances transformation efficiency, shortens the transformation cycle, and demonstrates broad genotype independence, providing a powerful tool for soybean research and breeding.

Glycine max↗

PubMed2026

Establishing a genetic mutation panel for predicting malignant transformation of oral leukoplakia: A prospective cohort study.

OBJECTIVE: To investigate somatic mutations in the whole genes of tissue samples from patients with oral leukoplakia (OLK), as the most typical precursor of oral cancer; and identify the specific genes as a mutational panel for predicting OLK malignant transformation. METHODS: A total of 123 consecutive OLK patients with long-term follow-up (median, 73 months) were prospectively enrolled, and divided into training set (n = 92) and independent test set (n = 31) based on chronological order of enrollment. Genomic DNA was isolated from the fresh-frozen biopsy tissues and somatic mutations in all genes were measured by whole-exome sequencing. RESULTS: We constructed a 3-gene (TP53, CASP8, and CYP2B6) mutational panel for risk stratification (any mutation vs. no mutation) of OLK malignant transformation. Kaplan-Meier analysis showed that the prognostic power of the 3-gene panel (log-rank P < 0.0001) for risk stratification in malignant progression was better than that of pathological grade in the training and test set, respectively. Multivariate Cox regression analysis revealed that this panel was an independent variable significantly associated with progression in the training (hazard ratio [HR] = 8.05; P < 0.001) and test set (HR = 11.26; P = 0.0421), respectively. The area under the curve (AUC) with 95 % confidence interval was 0.770 (0.648-0.892) and 0.877 (0.705-1.000) in the training and test set, respectively, for predicting malignant transformation in OLK patients. CONCLUSIONS: We established a 3-gene (TP53, CASP8, and CYP2B6) mutational panel as risk stratification model could effectively predict OLK malignant transformation, outperforming pathological grading-based assessment. Such genetic markers may provide a foundation for developing personalized management strategies.

Humans↗

PubMed2026

Unveiling a missing component of the atypical type IV secretion system required for natural transformation of Helicobacter pylori.

Exchange of genetic information by natural transformation shapes bacterial evolution. In Helicobacter pylori it is thought to drive its unusually high recombination rate, which has a crucial role in the evolution of virulence and the propagation of antibiotics resistance genes. While in most cases uptake of the incoming DNA into the periplasm is mediated by type IV pili, in H. pylori this initial step of natural transformation requires ComB, a unique competence-specific type IV secretion system (T4SS). The mechanisms by which ComB mediates DNA uptake are still poorly understood, since T4SS are usually involved in an opposite process of DNA export. Here, we identify a gene (hp1421) that is absolutely required for uptake of the transforming DNA into the periplasm, although distant from the comB operons. We show that hp1421 codes for a hexameric ATPase from the VirB11 family. HP1421 is present in the cytoplasm and interacts with ComB4, another ATPase of the T4SS inner membrane subcomplex. The structural modelling and functional analysis of HP1421 and its interaction with ComB4 indicate that HP1421 is a missing component of the ComB inner-membrane subcomplex that we propose to name ComB11. Phylogenetic analyses show that comB11 is a H. pylori core gene and suggest that the competence-dedicated ComB T4SS was a recent acquisition within Helicobacteraceae. Hence, co-option of the T4SS for DNA transformation requires nearly all the proteins that were previously essential for DNA conjugation.

Helicobacter pylori↗

PubMed2026

Advanced and underlying therapeutic strategies in transformed small cell lung cancer.

Transformed small-cell lung cancer (T-SCLC) is a clinically important form of histologic transformation and a mechanism of acquired resistance in non-small-cell lung cancer (NSCLC). It is associated with poor prognosis, with a median overall survival of only about 9-13 months. This review summarizes recent advances in the mechanisms, diagnosis, monitoring, and treatment of T-SCLC. Repeat biopsy remains the gold standard for confirming histologic transformation, whereas molecular profiling and liquid biopsy may facilitate early detection and longitudinal disease monitoring. Platinum-etoposide remains the most commonly used clinical standard after transformation, but its benefit is typically transient and durable disease control remains uncommon. Continuation of EGFR tyrosine kinase inhibitors combined with chemotherapy may prolong progression-free survival in selected patients but has not consistently improved overall survival. Anti-angiogenic therapy, particularly anlotinib, and chemo-immunotherapy have shown encouraging activity in selected patients, while emerging strategies targeting DLL3, MYC, SOX2, and epigenetic regulators may broaden the therapeutic landscape. Prospective studies integrating repeat tissue sampling, comprehensive genomic profiling, biomarker-guided patient stratification, pharmacogenomics, functional drug-sensitivity testing where feasible, and integrated multi-omics approaches are needed to advance molecularly guided and individualized treatment for T-SCLC.

advanced therapy↗

PubMed2025

Embed-Search-Align: DNA sequence alignment using Transformer models.

MOTIVATION: DNA sequence alignment, an important genomic task, involves assigning short DNA reads to the most probable locations on an extensive reference genome. Conventional methods tackle this challenge in two steps: genome indexing followed by efficient search to locate likely positions for given reads. Building on the success of Large Language Models in encoding text into embeddings, where the distance metric captures semantic similarity, recent efforts have encoded DNA sequences into vectors using Transformers and have shown promising results in tasks involving classification of short DNA sequences. Performance at sequence classification tasks does not, however, guarantee sequence alignment, where it is necessary to conduct a genome-wide search to align every read successfully, a significantly longer-range task by comparison. RESULTS: We bridge this gap by developing a "Embed-Search-Align" (ESA) framework, where a novel Reference-Free DNA Embedding (RDE) Transformer model generates vector embeddings of reads and fragments of the reference in a shared vector space; read-fragment distance metric is then used as a surrogate for sequence similarity. ESA introduces: (i) Contrastive loss for self-supervised training of DNA sequence representations, facilitating rich reference-free, sequence-level embeddings, and (ii) a DNA vector store to enable search across fragments on a global scale. RDE is 99% accurate when aligning 250-length reads onto a human reference genome of 3 gigabases (single-haploid), rivaling conventional algorithmic sequence alignment methods such as Bowtie and BWA-Mem. RDE far exceeds the performance of six recent DNA-Transformer model baselines such as Nucleotide Transformer, Hyena-DNA, and shows task transfer across chromosomes and species. AVAILABILITY AND IMPLEMENTATION: Please see https://anonymous.4open.science/r/dna2vec-7E4E/readme.md.

Sequence Analysis, DNA↗

PubMed2026

Unveiling a missing component of the atypical type IV secretion system required for natural transformation of Helicobacter pylori.

Journal Article↗

PubMed1987

One- and two-step transformations of rat thyroid epithelial cells by retroviral oncogenes.

A system of epithelial cells is described in which it is possible to study the number and the nature of genes capable of conferring the malignant phenotype. Two fully differentiated, hormone-responsive cell lines from rat thyroid glands are presented which are susceptible to one-step or two-step transformation upon infection with several murine acute retroviruses. After infection, both cell lines became independent from their thyrotropic hormone requirement for growth. However, complete transformation was achieved with one of the cell lines (FRTL-5 Cl 2), whereas the other cell line (PC Cl 3) failed to grow in agar and to give rise to tumors in vivo. The latter cell line was susceptible to complete transformation upon cooperation of the v-ras-Ha and the human c-myc oncogenes.

Animals↗

PubMed2026

A study on the directed engineering and multiple transformations of cannabidiolic acid synthase to enhance the expression level of the recombinant enzyme.

To increase the activity of cannabidiolic acid synthase (CBDAS) and its expression levels in yeast, this study focused on the CBDASG183V-N482W mutant. Using computer-aided techniques and literature reviews, four mutation sites were further identified, resulting in the mutant CBDASH114E-S116A-C176Y-G183V-N328Q-N482W. The CBDAS gene was integrated into the Pichia pastoris genome via multiple transformation rounds, and relative enzyme activity was analyzed using high-performance liquid chromatography. The results of the molecular docking analysis revealed factors such as increased intermolecular forces, shorter bond lengths, and an increased number of amino acid-substrate interaction sites, which may have contributed to the enhanced catalytic activity of the mutant. The concentrations of CBDA and CBD produced by the CBDASH114E-S116A-C176Y-G183V-N328Q-N482W mutant were 71.543 ng/mL and 75.163 ng/mL, respectively, which were 11.87% and 11.53% greater than those produced by the CBDASG183V-N482W mutant. The recombinant CBDAS strain obtained after two consecutive transformations of the CBDASH114E-S116A-C176Y-G183V-N328Q-N482W vector presented the highest CBDAS expression levels and CBD and CBDA yields; compared with those obtained after a single transformation, the CBDA and CBD yields increased by 9.77% and 12.65%, respectively. In addition, the tolerance of the recombinant strain to induction culture conditions was analyzed, revealing that the strain could be induced to express the protein at temperatures ranging from 20 to 45 °C and at pH values ranging from 3 to 9, with optimal expression observed at 30 °C and pH 6. These findings provide theoretical and technical support for the production of enzyme preparations for the in vitro-directed biosynthesis of cannabidiol.

Molecular Docking Simulation↗

PubMed2026

Predicting risk of ischemic stroke: A transformer model using genomic data.

BACKGROUND AND OBJECTIVE: Ischemic stroke is a leading cause of mortality and long-term disability worldwide. Genetic factors contribute to IS susceptibility, yet conventional polygenic risk score approaches are primarily based on additive effects and may not fully capture non-linear relationships or positional context and interactions among genetic variants. This study aimed to develop and evaluate a transformer-based genomic model incorporating position-wise genotype embedding for IS risk prediction. METHODS: We conducted a genome-wide association study using the UK Biobank dataset to identify IS-associated loci. Gene prioritisation was subsequently performed using tissue-specific expression quantitative trait locus-based Mendelian randomisation and colocalization analyses in whole blood and brain cortex. We then developed a transformer-based model that encoded genotype and SNP-position information using a position-wise embedding layer. Model performance was evaluated across three UK Biobank control definitions and externally assessed in the independent All of Us cohort. Performance metrics included the area under the receiver operating characteristic curve (AUROC), precision, recall, and F1 score. RESULTS: Across the three UK Biobank control definitions, the proposed method achieved the numerically highest discrimination among the evaluated models, with AUROCs of 0.8109, 0.7843, and 0.7468 using MRF-negative, combined, and MRF-positive controls, respectively. In the external All of Us cohort, the proposed method achieved an AUROC of 0.7251 and retained the highest AUROC among the evaluated models. In a separate incident-stroke survival analysis, medium- and high-score groups had hazard ratios of 1.13 and 1.21, respectively, relative to the low-score group. A total of 18 IS-associated loci were identified. Among the tissue-specific MR results, EDEM2 in the brain cortex remained significant after Bonferroni correction, while DCHS2 showed a nominal association. CONCLUSIONS: The proposed transformer-based framework provides a genomic modelling approach that achieved the highest discrimination among the evaluated models in this study and retained comparative performance in an independent external cohort. In further applications, integrating this genomic framework with conventional clinical, lifestyle, and environmental risk factors may support more comprehensive and personalised IS risk assessment. Prospective, population-representative, and multi-ancestry validation will be important to establish its potential role in future prevention-oriented risk management.

Genomics and bioinformatics↗

PubMed2024

Binary vector copy number engineering improves Agrobacterium-mediated transformation.

The copy number of a plasmid is linked to its functionality, yet there have been few attempts to optimize higher-copy-number mutants for use across diverse origins of replication in different hosts. We use a high-throughput growth-coupled selection assay and a directed evolution approach to rapidly identify origin of replication mutations that influence copy number and screen for mutants that improve Agrobacterium-mediated transformation (AMT) efficiency. By introducing these mutations into binary vectors within the plasmid backbone used for AMT, we observe improved transient transformation of Nicotiana benthamiana in four diverse tested origins (pVS1, RK2, pSa and BBR1). For the best-performing origin, pVS1, we isolate higher-copy-number variants that increase stable transformation efficiencies by 60-100% in Arabidopsis thaliana and 390% in the oleaginous yeast Rhodosporidium toruloides. Our work provides an easily deployable framework to generate plasmid copy number variants that will enable greater precision in prokaryotic genetic engineering, in addition to improving AMT efficiency.

Genetic Vectors↗

PubMed2026

HRAS promotes mutant NRAS-driven transformation with codon and allele specificity.

Wild-type RAS family members determine the signaling and therapeutic response in cancers driven by mutant HRAS and KRAS because they activate alternate RAS effector pathways. Here, we found that the requirement for wild-type RAS to support mutant NRAS-driven transformation correlated with codon-specific differences in GTP hydrolysis. NRAS with mutations at either Gly12 (G12X) or Gly13 (G13X), which retained the GDP-GTP cycling function, had modest autonomous transforming potential. In contrast, NRAS with GTP-locking mutations at Gln61 (Q61X mutants) was uncoupled from receptor tyrosine kinase (RTK) input, rendering wild-type RAS an obligate partner for RTK-stimulated signaling and oncogenesis. In RASless cells expressing mutant NRAS, reintroduction of wild-type HRAS was sufficient to restore signaling and transformation. Global dependency mapping in human cancer cells revealed functional partitioning, wherein mutant NRAS promoted MAPK signaling and wild-type HRAS promoted PI3K-AKT survival signaling. Consequently, allele-specific or pan-RAS(ON) inhibitors synergized with inhibitors of proximal RTK signaling or of wild-type HRAS or KRAS to overcome this signaling plasticity. Pan-RAS(ON) and HRAS inhibition was synergistic for all NRAS mutants tested, with Q61X mutants showing greater sensitivity. These findings define the signaling partnership between mutant NRAS and wild-type HRAS as a targetable vulnerability and provide a biochemical blueprint for dual RAS inhibition in NRAS-mutated malignancies.

Humans↗

PubMed2026

Systematic evaluation of one-dimensional-to-two-dimensional near-infrared spectroscopy transformations with deep learning for quantifying coconut sap adulteration.

Near-infrared (NIR) spectroscopy have limitations when combined with deep learning (DL) algorithms because they rely on low-dimensional datasets. Therefore, we investigated the potential of transforming one-dimensional (1D) NIR spectra into two-dimensional (2D) spectrograms using synchronous and asynchronous techniques and the continuous wavelet transform (CWT) and their effectiveness by integrating with DL for detecting adulteration in coconut sap. NIR spectra (12,500-4000 cm-1) were collected from binary mixtures (0%-100%;w/w). The performance of all DL (convolutional neural networks-CNN, AlexNet and ResNet) models was compared with that of partial least squares (PLS). The models were ranked in the mentioned order based on their performances: 2D-CWT > 2D-asynchronous > 2D-synchronous > 1D/2D-PLS. The important features of the best model can be explained and visualized using gradient-weighted-class-activation-mapping. The findings highlight that the 1D-to-2D NIR data transformation combined with DL is a highly robust approach because it addresses the feature representation gap in NIR data and effectively captures the spatial-spectral correlations.

Spectroscopy, Near-Infrared↗

PubMed2026

Viral mimicry escape as a necessary feature of malignant transformation.

Malignant transformation is driven by disruption of pathways regulating proliferation and cell fate, but these same disruptions can create a collateral vulnerability: loss of transcriptional and epigenetic control over transposable elements and other normally silenced genomic regions. Consequently, emerging cancer cells can accumulate transposable element-derived and other endogenous immunogenic nucleic acids capable of triggering antiviral responses, a process termed viral mimicry. Increasing evidence indicates that viral mimicry can eliminate precancerous cells and shape tumour evolution, positioning it as an intrinsic tumour-suppressive mechanism. Here we highlight how cancer-associated changes in DNA methylation, histone modifications, splicing and RNA processing can lead to the presence of immunogenic nucleic acids that can activate viral mimicry pathways. We outline how cancer cells suppress viral mimicry, including compensatory epigenetic repression, RNA editing, nucleic acid decay and dampening of interferon signalling to enable cancer cell growth. Finally, we highlight the evidence suggesting that escaping viral mimicry is a fundamental process for cancer initiation and progression, and suggest that viral mimicry escape is necessary for cancer transformation and a therapeutic target in combination with immunotherapies. By framing viral mimicry escape as a necessary part of cancer transformation, this Review provides a unifying conceptual model for its translational exploitation.

Journal Article↗

PubMed2025

Foundation model based multimodal transformer framework for survival analysis in HER2 stratified breast cancer.

Objective. To improve survival prediction for HER2-positive breast cancer by integrating histopathological, molecular, and clinical data using a multimodal transformer framework.Approach. We propose a multimodal transformer framework for breast cancer survival prediction using HER2 stratified (SurvMBC), a foundation model-enhanced architecture that fuses three data modalities: whole-slide images, clinical narratives, and molecular features. Tumor microenvironment features are extracted using a pathology language and image pre-training (PLIP), clinical narratives are processed with BioBERT, and miRNA expression plus DNA methylation data are embedded using Gen2Vec. These representations are integrated through a cross-modal transformer with attention mechanisms for survival prediction.Main results. The model was evaluated on 1,095 HER2-positive breast cancer patients from The Cancer Genome Atlas. SurvMBC achieved a concordance index (C-index) of 0.857 (95% CI: 0.834, 0.880), a low integrated Brier score, and a strong inverse negative binomial log-likelihood. Risk stratification based on model outputs significantly separated high- and low-risk groups (log-rankp< 0.01) and showed strong associations with tumor stage, grade, and hormone receptor status (allp< 0.05).Significance. SurvMBC demonstrates the effectiveness of multimodal fusion in addressing tumor heterogeneity and improving prognostic accuracy. The attention-based integration enables context-aware learning of survival-relevant features across modalities, supporting individualized risk stratification and risk-adaptive treatment planning for HER2 stratified breast cancer patients.

Breast Neoplasms↗