Modeling Agrobacterium-Mediated Gene Transformation of Tobacco (Nicotiana tabacum)-A Model Plant for Gene Transformation Studies

Functional analysis of NtPDX2 in Nicotiana tabacum L. associated with stem development

Vitamin B6 is a water-soluble vitamin that is essential for all living organisms in their life activities. Among its forms, pyridoxal 5'-phosphate (PLP) is the primary metabolically active form of Vitamin B6, which usually plays a crucial role in the metabolism of proteins, fatty acids, and carbohydrates. To date, although the molecular functions of genes involved in vitamin B6 biosynthesis, including Pdx1, Pdx2, Pdx3, and Sos4, have been reported in various plants, no studies have yet explored the functions of NtPDX1 and NtPDX2 in tobacco. This study used the Nicotiana tabacum L. as material to clone the CDS sequence of the NtPDXs. Through bioinformatics analysis, we predicted the phylogenetic relationships and functions of these genes; the subcellular localization of NtPDX2 was found to be in the cytoplasmic structures. By conducting both constitutive overexpression and homozygous knockout studies of the NtPDX2, we observed a significant increase in vitamin B6 content in the stem tissues of overexpressing plants (up to 150%), while knockout plants showed a decrease to 60%. This led to changes in agronomic traits such as plant height and stem thickness in tobacco plants. The overexpressing plants exhibited a significant increase in height (100.93 cm) and stem thickness (13.64 cm), whereas the knockout plants were shorter in height (73.10 cm) and had thinner stems (10.83 cm). By integrating transcriptome sequencing technology with molecular biology methods, we aim to elucidate the molecular mechanisms underlying the role of NtPDX2 in tobacco growth and development, thereby providing new genetic resources and a theoretical foundation for the cultivation of new tobacco varieties with superior quality for flue-cured tobacco.

The regulation of auxin receptor gene CsAFB2 by csn-miR393a confers resistance against Colletotrichum gloeosporioides in tea plants

Anthracnose, a severe disease caused by Colletotrichum, affects diverse crops and leads to significant economic losses through pronounced fruit/leaf lesions. MicroRNAs (miRNAs) play crucial roles in modulating gene expression in response to disease resistance, defence responses and plant immunity. However, the regulatory mechanisms of miRNAs in responses to Colletotrichum gloeosporioides remain unknown in tea plants. Our study revealed that csn-miR393a targets auxin receptor gene CsAFB2 during resistance to C. gloeosporioides in tea plants by comparing the resistant cultivar Zhongcha108 to the susceptible cultivar Longjing43. Through Nicotiana benthamiana leaf co-transformation assays, we demonstrated that csn-miR393a suppresses the expression of CsAFB2, and csn-miR393a target mimic blocks the function of csn-miR393a, leading to increase in the expression of CsAFB2. Repression of transcripts in tea leaves by antisense oligonucleotides demonstrated that csn-miR393a negatively affects the tea plant defence by regulating reactive oxygen species homoeostasis, PR gene expression and catechin accumulation. To further validate the regulatory mechanisms of csn-miR393a, we developed transgenic tea plants overexpressing CsAFB2, resulting in enhanced resistance responses against C. gloeosporioides. Additionally, transgenic N. benthamiana lines overexpressing a csn-miR393a target mimic provided further evidence that csn-miR393a negatively regulates the tea plant defence response against C. gloeosporioides by suppressing CsAFB2. Therefore, manipulating csn-miR393a or its target gene, CsAFB2, has the potential to strengthen the tea plant's resistance against tea anthracnose.

Mediated Transformation of Tamarillo (Solanum betaceum) Callus Cell Suspension Cultures: A Novel Platform for Biotechnological Applications

Solanum betaceum Cav. (tamarillo) has a strong biotechnological potential given the ease of obtaining cell lines from it that can be genetically transformed. However, genetic transformation of tamarillo cell suspension cultures has not yet been described. This study presents a simple method for Agrobacterium-mediated transformation of these cells and demonstrates the successful insertion of the β-glucuronidase gene (gusA) and the yellow fluorescent protein gene (eyfp) in their genome. For the success of this protocol, the selection of actively growing sub-cultured callus as explant and isolation of bacterial colonies with a cell density OD600 of 0.6-0.8 were key steps. Also, the inoculation of the callus in a bacteria liquid culture, the use of sonication, and the addition of antioxidants were essential. The transient expression of the gusA gene in tamarillo callus was confirmed and quantified, and no significant differences were observed between using LBA4404 or EHA105 strains. Finally, the insertion of the eyfp gene in the tamarillo genome enabled the in vivo confirmation of the transformation success. The present study showed that tamarillo cell suspension cultures can be genetically modified, opening the way for metabolite production in transformed cells and future scaling-up in bioreactors.

J, Kaushik M, Mulani E, S. M, Roy J, Phogat S, Sareen B, Madhavan J, Sevanthi AM, Solanke AU, Kumar P, Mandal PK. Low titre of agroinoculum with prolonged incubation period and low auxin concentration in the regeneration media are the key to high frequency of transformation in climate-resilient Aus-type rice genotype Nagina 22

Developing an efficient and reproducible regeneration protocol holds paramount significance for advancing genetic transformation technologies in rice, facilitating their utilisation in crop improvement. Nagina 22 (N22), a climate-resilient Aus-type rice genotype known for its tolerance against multiple stresses, lacks a standardised transformation protocol, limiting its utilisation as a background for genetic transformation. This study reports, for the first time, a highly efficient transformation and regeneration protocol for N22 using a CRISPR/Cas9 vector. Mature seeds were used to induce embryogenic calli on CHU(N6)-based callus induction media (CIM) with varying concentrations of 2,4-dichlorophenoxyacetic acid (2,4-D). The highest callus induction efficiency (~ 94%) was achieved using 3 mgL-1 2,4-D. For regeneration, calli were transferred to different regeneration media-I (RM-Ia to RM-Ie), where a combination of 5 mgL-1 6-benzylaminopurine (BAP) and 0.02 mgL-1 naphthalene acetic acid (NAA) resulted in ~ 44% regeneration frequency. Subsequent optimisation of regeneration media-II (RM-II) with low NAA concentration enhanced shoot elongation and root development. Furthermore, reducing basal salt concentration in the resuspension media significantly enhanced transformation efficiency to 44%, achieved, by only using sterile distilled water (SDW) with 150 mM acetosyringone for calli infection. The optimised protocol was successfully validated using CRISPR/Cas9 vector, facilitating targeted gene knockouts for functional genomic studies. This approach addresses a critical gap in N22 genetic transformation, providing a reliable protocol for advancing rice improvement through gene editing. It offers valuable insights for future research and practical applications in genetic transformation of this elite rice genotype for various agronomic and scientific purposes.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13205-025-04210-y.

Prospects for synthetic biology in 21st Century agriculture

Plant synthetic biology has emerged as a transformative field in agriculture, offering innovative solutions to enhance food security, provide resilience to climate change, and transition to sustainable farming practices. By integrating advanced genetic tools, computational modeling, and systems biology, researchers can precisely modify plant genomes to enhance traits such as yield, stress tolerance, and nutrient use efficiency. The ability to design plants with specific characteristics tailored to diverse environmental conditions and agricultural needs holds great potential to address global food security challenges. Here, we highlight recent advancements and applications of plant synthetic biology in agriculture, focusing on key areas such as photosynthetic efficiency, nitrogen fixation, drought tolerance, pathogen resistance, nutrient use efficiency, biofortification, climate resilience, microbiology engineering, synthetic plant genomes, and the integration of artificial intelligence (AI) with synthetic biology. These innovations aim to maximize resource use efficiency, reduce reliance on external inputs, and mitigate environmental impacts associated with conventional agricultural practices. Despite challenges related to regulatory approval and public acceptance, the integration of synthetic biology in agriculture holds immense promise for creating more resilient and sustainable agricultural systems, contributing to global food security and environmental sustainability. Rigorous multi-field testing of these approaches will undoubtedly be required to ensure reproducibility.

Preliminary assessment of seed heteromorfism as an adaptive strategy of Colobanthus quitensis under saline conditions

Colobanthus quitensis is known for enduring extreme conditions, such as high salinity in Antarctica, making it an excellent model for studying environmental stress. In plant families, variations in seed color heteromorphism have been linked to various germination under stress conditions. Preliminary laboratory observations indicated that dark brown seeds of C. quitensis had higher germination rates, suggesting that this phenotypic trait might offer a germination advantage, particularly under saline conditions. To investigate this, germination of heteromorphic seeds from Antarctic, sub-Antarctic, and Andean populations of C. quitensis was assessed under in vitro saline conditions. Among all populations, dark brown seeds exhibited greater germination and shorter germination time than other seeds in the absence of salinity. In the Antarctic population, dark brown seeds showed better salinity tolerance. In the sub-Antarctic La Marisma population, salt tolerance was not affect by seed color, showing the population was the most salt-tolerant. The other two populations showed very low germination even at low salinity concentration. This study is the first scientific report of seed heteromorphism in C. quitensis populations, offering insights into mechanisms of salinity tolerance and potentially other stress conditions that enhance the species' resilience. In addition, the identification of La Marisma populations as a salinity-tolerant population will holds biotechnological importance for agriculture.

Promoter of Vegetable Pea PsPIP2-4 Responds to Abiotic Stresses in Transgenic Tobacco

Plasma membrane intrinsic proteins (PIPs), one sub-family of aquaporins (AQPs), are responsible for plant abiotic stress responses. However, little information is currently available about the stress responsiveness of the PIP promoter in vegetable pea. In the present study, one novel promoter of PsPIP2-4 which shared high similarity to the PIP2-type AQPs from other plants, was isolated. Quantitative real-time PCR (qRT-PCR) assays suggested that PsPIP2-4 was predominantly expressed in leaves and abundantly induced by abiotic stress treatments (polyethylene glycol (PEG) 6000, NaCl, and methyl jasmonate (MeJA)). Further, the promoter activity of PsPIP2-4 was verified in transgenic tobacco plants. Beta-glucuronidase (GUS) staining driven by the PsPIP2-4 promoter confirmed that it was mainly detected in the leaves of transgenic seedlings, especially in the guard cells. Exposure of transgenic seedlings to various environmental stimuli proved that the promoter activity of PsPIP2-4 was abundantly strengthened by osmotic, salt, and MeJA stresses. This research provides one stress-inducible promoter enabling targeted gene expression under abiotic stresses and demonstrates its usefulness in the genetic improvement of plant stress resistance.

Establishment of Agrobacterium-Mediated Transient Transformation System in Desert Legume Eremosparton songoricum (Litv.) Vass

Eremosparton songoricum (Litv.) Vass. is a desert legume exhibiting extreme drought tolerance and the ability to withstand various harsh environments, making it a good candidate for investigating stress tolerance mechanisms and exploring valuable stress-resistant genes. However, the absence of a genetic transformation system for E. songoricum poses significant limitations for functionally validating these stress-resistant genes in situ. In this study, we developed an Agrobacterium-mediated transient transformation system for E. songoricum utilizing the β-glucuronidase (GUS) gene as a reporter. We investigated three types of explants (seedlings, assimilated branches and callus) and the effects of different Agrobacterium strains, seedling ages, OD600 values, acetosyringone (AS) concentrations, sucrose concentrations and infection times on the transformation efficiency. The results reveal that the optimal transformation system was infecting one-month-old regenerating assimilated branches with the Agrobacterium strain C58C1. The infection solution comprised 1/2 MS medium with 3% sucrose and 200 μM AS at an OD600 of 0.8, infection for 3 h and then followed by 2 days of dark cultivation, which achieving a maximum transformation rate of 97%. The maximum transformation rates of the seedlings and calluses were 57.17% and 39.51%, respectively. Moreover, we successfully utilized the assimilated branch transient transformation system to confirm the role of the previously reported transcription factor EsDREB2B in E. songoricum. The overexpression of EsDREB2B enhanced drought tolerance by increasing the plant's reactive oxygen species (ROS) scavenging capacity in situ. This study established the first transient transformation system for a desert legume woody plant, E. songoricum. This efficient system can be readily applied to investigate gene functions in E. songoricum. It will expedite the exploration of genetic resources and stress tolerance mechanisms in this species, offering valuable insights and serving as a reference for the transformation of other desert plants and woody legumes.

Genotype-specific responses to in vitro drought stress in myrtle (Myrtus communis L.): integrating machine learning techniques

Background

Myrtle (Myrtus communis L.), native to the Mediterranean region of Türkiye, is a valuable plant with applications in traditional medicine, pharmaceuticals, and culinary practices. Understanding how myrtle responds to water stress is essential for sustainable cultivation as climate change exacerbates drought conditions.

Methods

This study investigated the performance of selected myrtle genotypes under in vitro drought stress by employing tissue culture techniques, rooting trials, and acclimatization processes. Genotypes were tested under varying polyethylene glycol (PEG) concentrations (1%, 2%, 4%, and 6%). Machine learning (ML) algorithms, including Gaussian process (GP), support vector machine (SVM), Random Forest (RF), and Extreme Gradient Boosting (XGBoost), were utilized to model and predict micropropagation and rooting efficiency.

Results

The research revealed a genotype-dependent response to drought stress. Black-fruited genotypes exhibited higher micropropagation rates compared to white-fruited ones under stress conditions. The application of ML models successfully predicted micropropagation and rooting efficiency, providing insights into genotype performance.

Conclusions

The findings suggest that selecting drought-tolerant genotypes is crucial for enhancing myrtle cultivation. The results underscore the importance of genotype selection and optimization of cultivation practices to address climate change impacts. Future research should explore the molecular mechanisms of stress responses to refine breeding strategies and improve resilience in myrtle and similar economically important crops.

Efficient Regeneration of Transgenic Rice from Embryogenic Callus via Agrobacterium-Mediated Transformation: A Case Study Using GFP and Apple MdFT1 Genes

Genetic transformation is a critical tool for gene manipulation and functional analyses in plants, enabling the exploration of key phenotypes and agronomic traits at the genetic level. While dicotyledonous plants offer various tissues for in vitro culture and transformation, monocotyledonous plants, such as rice, have limited options. This study presents an efficient method for genetically transforming rice (Oryza sativa L.) using seed-derived embryogenic calli as explants. Two target genes were utilized to assess regeneration efficiency: green fluorescent protein (eGFP) and the apple FLOWERING LOCUS T (FT)-like gene (MdFT1). Antisense MdFT1 was cloned into a vector controlled by the rice α-amylase 3D (Ramy3D) promoter, while eGFP was fused to Cas9 under the Ubi promoter. These vectors were introduced separately into rice embryogenic calli from two Korean cultivars using Agrobacterium-mediated transformation. Transgenic seedlings were successfully regenerated via hygromycin selection using an in vitro cultivation system. PCR confirmed stable transgene integration in the transgenic calli and their progeny. Fluorescence microscopy revealed eGFP expression, and antisense MdFT1-expressing lines exhibited notable phenotypic changes, including variations in plant height and grain quality. High transformation efficiency and regeneration frequency were achieved for both tested cultivars. This study demonstrated the effective use of seed-derived embryogenic calli for rice transformation, offering a promising approach for developing transgenic plants in monocot species.

Choosing an appropriate somatic embryogenesis medium of carrot (Daucus carota L.) by data mining technology

INTRODUCTION

Developing somatic embryogenesis is one of the main steps in successful in vitro propagation and gene transformation in the carrot. However, somatic embryogenesis is influenced by different intrinsic (genetics, genotype, and explant) and extrinsic (e.g., plant growth regulators (PGRs), medium composition, and gelling agent) factors which cause challenges in developing the somatic embryogenesis protocol. Therefore, optimizing somatic embryogenesis is a tedious, time-consuming, and costly process. Novel data mining approaches through a hybrid of artificial neural networks (ANNs) and optimization algorithms can facilitate modeling and optimizing in vitro culture processes and thereby reduce large experimental treatments and combinations. Carrot is a model plant in genetic engineering works and recombinant drugs, and therefore it is an important plant in research works. Also, in this research, for the first time, embryogenesis in carrot (Daucus carota L.) using Genetic algorithm (GA) and data mining technology has been reviewed and analyzed.

MATERIALS AND METHODS

In the current study, data mining approach through multilayer perceptron (MLP) and radial basis function (RBF) as two well-known ANNs were employed to model and predict embryogenic callus production in carrot based on eight input variables including carrot cultivars, agar, magnesium sulfate (MgSO4), calcium dichloride (CaCl2), manganese (II) sulfate (MnSO4), 2,4-dichlorophenoxyacetic acid (2,4-D), 6-benzylaminopurine (BAP), and kinetin (KIN). To confirm the reliability and accuracy of the developed model, the result obtained from RBF-GA model were tested in the laboratory.

RESULTS

The results showed that RBF had better prediction efficiency than MLP. Then, the developed model was linked to a genetic algorithm (GA) to optimize the system. To confirm the reliability and accuracy of the developed model, the result of RBF-GA was experimentally tested in the lab as a validation experiment. The result showed that there was no significant difference between the predicted optimized result and the experimental result.

CONCLUTIONS

Generally, the results of this study suggest that data mining through RBF-GA can be considered as a robust approach, besides experimental methods, to model and optimize in vitro culture systems. According to the RBF-GA result, the highest somatic embryogenesis rate (62.5%) can be obtained from Nantes improved cultivar cultured on medium containing 195.23 mg/l MgSO4, 330.07 mg/l CaCl2, 18.3 mg/l MnSO4, 0.46 mg/l 2,4- D, 0.03 mg/l BAP, and 0.88 mg/l KIN. These results were also confirmed in the laboratory.

Agrobacterium tumefaciens-Mediated Plant Transformation: A Review

Agrobacterium tumefaciens-mediated plant transformation is the most dominant technique for the transformation of plants. It is used to transform monocotyledonous and dicotyledonous plants. A. tumefaciens apply for stable and transient transformation, random and targeted integration of foreign genes, as well as genome editing of plants. The Advantages of this method include cheapness, uncomplicated operation, high reproducibility, a low copy number of integrated transgenes, and the possibility of transferring larger DNA fragments. Engineered endonucleases such as CRISPR/Cas9 systems, TALENs, and ZFNs can be delivered with this method. Nowadays, Agrobacterium-mediated transformation is used for the Knock in, Knock down, and Knock out of genes. The transformation effectiveness of this method is not always desirable. Researchers applied various strategies to improve the effectiveness of this method. Here, a general overview of the characteristics and mechanism of gene transfer with Agrobacterium is presented. Advantages, updated data on the factors involved in optimizing this method, and other useful materials that lead to maximum exploitation as well as overcoming obstacles of this method are discussed. Moreover, the application of this method in the generation of genetically edited plants is stated. This review can help researchers to establish a rapid and highly effective Agrobacterium-mediated transformation protocol for any plant species.

Leveraging machine learning to unravel the impact of cadmium stress on goji berry micropropagation

This study investigates the influence of cadmium (Cd) stress on the micropropagation of Goji Berry (Lycium barbarum L.) across three distinct genotypes (ERU, NQ1, NQ7), employing an array of machine learning (ML) algorithms, including Multilayer Perceptron (MLP), Support Vector Machines (SVM), Random Forest (RF), Gaussian Process (GP), and Extreme Gradient Boosting (XGBoost). The primary motivation is to elucidate genotype-specific responses to Cd stress, which poses significant challenges to agricultural productivity and food safety due to its toxicity. By analyzing the impacts of varying Cd concentrations on plant growth parameters such as proliferation, shoot and root lengths, and root numbers, we aim to develop predictive models that can optimize plant growth under adverse conditions. The ML models revealed complex relationships between Cd exposure and plant physiological changes, with MLP and RF models showing remarkable prediction accuracy (R2 values up to 0.98). Our findings contribute to understanding plant responses to heavy metal stress and offer practical applications in mitigating such stress in plants, demonstrating the potential of ML approaches in advancing plant tissue culture research and sustainable agricultural practices.

Optimizing PGRs for in vitro shoot proliferation of pomegranate with bayesian-tuned ensemble stacking regression and NSGA-II: a comparative evaluation of machine learning models

BACKGROUND

The process of optimizing in vitro shoot proliferation is a complicated task, as it is influenced by interactions of many factors as well as genotype. This study investigated the role of various concentrations of plant growth regulators (zeatin and gibberellic acid) in the successful in vitro shoot proliferation of three Punica granatum cultivars ('Faroogh', 'Atabaki' and 'Shirineshahvar'). Also, the utility of five Machine Learning (ML) algorithms-Support Vector Regression (SVR), Random Forest (RF), Extreme Gradient Boosting (XGB), Ensemble Stacking Regression (ESR) and Elastic Net Multivariate Linear Regression (ENMLR)-as modeling tools were evaluated on in vitro multiplication of pomegranate. A new automatic hyperparameter optimization method named Adaptive Tree Pazen Estimator (ATPE) was developed to tune the hyperparameters. The performance of the models was evaluated and compared using statistical indicators (MAE, RMSE, RRMSE, MAPE, R and R2), while a specific Global Performance Indicator (GPI) was introduced to rank the models based on a single parameter. Moreover, Non‑dominated Sorting Genetic Algorithm‑II (NSGA‑II) was employed to optimize the selected prediction model.

RESULTS

The results demonstrated that the ESR algorithm exhibited higher predictive accuracy in comparison to other ML algorithms. The ESR model was subsequently introduced for optimization by NSGA‑II. ESR-NSGA‑II revealed that the highest proliferation rate (3.47, 3.84, and 3.22), shoot length (2.74, 3.32, and 1.86 cm), leave number (18.18, 19.76, and 18.77), and explant survival (84.21%, 85.49%, and 56.39%) could be achieved with a medium containing 0.750, 0.654, and 0.705 mg/L zeatin, and 0.50, 0.329, and 0.347 mg/L gibberellic acid in the 'Atabaki', 'Faroogh', and 'Shirineshahvar' cultivars, respectively.

CONCLUSIONS

This study demonstrates that the 'Shirineshahvar' cultivar exhibited lower shoot proliferation success compared to the other cultivars. The results indicated the good performance of ESR-NSGA-II in modeling and optimizing in vitro propagation. ESR-NSGA-II can be applied as an up-to-date and reliable computational tool for future studies in plant in vitro culture.

Machine learning-mediated Passiflora caerulea callogenesis optimization

Callogenesis is one of the most powerful biotechnological approaches for in vitro secondary metabolite production and indirect organogenesis in Passiflora caerulea. Comprehensive knowledge of callogenesis and optimized protocol can be obtained by the application of a combination of machine learning (ML) and optimization algorithms. In the present investigation, the callogenesis responses (i.e., callogenesis rate and callus fresh weight) of P. caerulea were predicted based on different types and concentrations of plant growth regulators (PGRs) (i.e., 2,4-dichlorophenoxyacetic acid (2,4-D), 6-benzylaminopurine (BAP), 1-naphthaleneacetic acid (NAA), and indole-3-Butyric Acid (IBA)) as well as explant types (i.e., leaf, node, and internode) using multilayer perceptron (MLP). Moreover, the developed models were integrated into the genetic algorithm (GA) to optimize the concentration of PGRs and explant types for maximizing callogenesis responses. Furthermore, sensitivity analysis was conducted to assess the importance of each input variable on the callogenesis responses. The results showed that MLP had high predictive accuracy (R2 > 0.81) in both training and testing sets for modeling all studied parameters. Based on the results of the optimization process, the highest callogenesis rate (100%) would be obtained from the leaf explant cultured in the medium supplemented with 0.52 mg/L IBA plus 0.43 mg/L NAA plus 1.4 mg/L 2,4-D plus 0.2 mg/L BAP. The results of the sensitivity analysis showed the explant-dependent impact of the exogenous application of PGRs on callogenesis. Generally, the results showed that a combination of MLP and GA can display a forward-thinking aid to optimize and predict in vitro culture systems and consequentially cope with several challenges faced currently in Passiflora tissue culture.

Prediction and optimization of indirect shoot regeneration of Passiflora caerulea using machine learning and optimization algorithms

BACKGROUND

Optimization of indirect shoot regeneration protocols is one of the key prerequisites for the development of Agrobacterium-mediated genetic transformation and/or genome editing in Passiflora caerulea. Comprehensive knowledge of indirect shoot regeneration and optimized protocol can be obtained by the application of a combination of machine learning (ML) and optimization algorithms.

MATERIALS AND METHODS

In the present investigation, the indirect shoot regeneration responses (i.e., de novo shoot regeneration rate, the number of de novo shoots, and length of de novo shoots) of P. caerulea were predicted based on different types and concentrations of PGRs (i.e., TDZ, BAP, PUT, KIN, and IBA) as well as callus types (i.e., callus derived from different explants including leaf, node, and internode) using generalized regression neural network (GRNN) and random forest (RF). Moreover, the developed models were integrated into the genetic algorithm (GA) to optimize the concentration of PGRs and callus types for maximizing indirect shoot regeneration responses. Moreover, sensitivity analysis was conducted to assess the importance of each input variable on the studied parameters.

RESULTS

The results showed that both algorithms (RF and GRNN) had high predictive accuracy (R² > 0.86) in both training and testing sets for modeling all studied parameters. Based on the results of optimization process, the highest de novo shoot regeneration rate (100%) would be obtained from callus derived from nodal segments cultured in the medium supplemented with 0.77 mg/L BAP plus 2.41 mg/L PUT plus 0.06 mg/L IBA. The results of the sensitivity analysis showed the explant-dependent impact of exogenous application of PGRs on indirect de novo shoot regeneration.

CONCLUSIONS

A combination of ML (GRNN and RF) and GA can display a forward-thinking aid to optimize and predict in vitro culture systems and consequentially cope with several challenges faced currently in Passiflora tissue culture.

CRISPR/Cas9 and Agrobacterium tumefaciens virulence proteins synergistically increase efficiency of precise genome editing via homology directed repair in plants

CRISPR/Cas9 genome editing and Agrobacterium tumefaciens-mediated genetic transformation are widely-used plant biotechnology tools derived from bacterial immunity-related systems, each involving DNA modification. The Cas9 endonuclease introduces DNA double-strand breaks (DSBs), and the A. tumefaciens T-DNA is released by the VirD2 endonuclease assisted by VirDl and attached by VirE2, transferred to the plant nucleus and integrated into the genome. Here, we explored the potential for synergy between the two systems and found that Cas9 and three virulence (Vir) proteins achieve precise genome editing via the homology directed repair (HDR) pathway in tobacco and rice plants. Compared with Cas9T (Cas9, VirD1, VirE2) and CvD (Cas9-VirD2) systems, the HDR frequencies of a foreign GFPm gene in the CvDT system (Cas9-VirD2, VirD1, VirE2) increased 52-fold and 22-fold, respectively. Further optimization of the CvDT process with a donor linker (CvDTL) achieved a remarkable increase in the efficiency of HDR-mediated genome editing. Additionally, the HDR efficiency of the three rice endogenous genes ACETOLACTATE SYNTHASE (ALS), PHYTOENE DESATURASE (PDS), and NITROGEN TRANSPORTER 1.1 B (NRT1.1B) increased 24-, 32- and 16-fold, respectively, in the CvDTL system, compared with corresponding Cas9TL (Cas9T process with a donor linker). Our results suggest that collaboration between CRISPR/Cas9 and Agrobacterium-mediated genetic transformation can make great progress towards highly efficient and precise genome editing via the HDR pathway.

Comparative analysis of different artificial neural networks for predicting and optimizing in vitro seed germination and sterilization of petunia

The process of optimizing in vitro seed sterilization and germination is a complicated task since this process is influenced by interactions of many factors (e.g., genotype, disinfectants, pH of the media, temperature, light, immersion time). This study investigated the role of various types and concentrations of disinfectants (i.e., NaOCl, Ca(ClO)2, HgCl2, H2O2, NWCN-Fe, MWCNT) as well as immersion time in successful in vitro seed sterilization and germination of petunia. Also, the utility of three artificial neural networks (ANNs) (e.g., multilayer perceptron (MLP), radial basis function (RBF), and generalized regression neural network (GRNN)) as modeling tools were evaluated to analyze the effect of disinfectants and immersion time on in vitro seed sterilization and germination. Moreover, non‑dominated sorting genetic algorithm‑II (NSGA‑II) was employed for optimizing the selected prediction model. The GRNN algorithm displayed superior predictive accuracy in comparison to MLP and RBF models. Also, the results showed that NSGA‑II can be considered as a reliable multi-objective optimization algorithm for finding the optimal level of disinfectants and immersion time to simultaneously minimize contamination rate and maximize germination percentage. Generally, GRNN-NSGA-II as an up-to-date and reliable computational tool can be applied in future plant in vitro culture studies.

Identification and functional analysis of calcium sensor calmodulins from heavy metal hyperaccumulator Noccaea caerulescens

Noccaea caerulescens (J. Presl & C. Presl) F. K. Mey. is a heavy metal hyperaccumulator exhibiting extreme tolerance to various environmental stresses. To date, the functional role of Ca2+ -binding protein in this plant is largely unknown. To investigate the function of calmodulins (CaMs) in N. caerulescens , CaM2 , a Ca2+ sensor encoding gene, was identified and functionally characterised. Protein structure analysis showed that NcCaM2 contains four classic exchange factor (EF)-hand motifs with high sequence similarity to the CaM proteins from model plant Arabidopsis thaliana L. Tissue specific expression analysis showed that NcCaM2 is constitutively expressed in stems, leaves, and roots. Expression level of NcCaM2 was significantly upregulated under various environmental stimulus, indicating a potential involvement of NcCaM2 in the tolerance to abiotic stresses. The heterologous expression of NcCaM2 in a yeast mutant strain increased the heavy metal tolerance in yeast cells. Furthermore, the constitutive expression of NcCaM2 enhanced the heavy metal tolerance capability of transgenic tobacco (Nicotiana tabacum L.) plants. Our data suggested an important role of NcCaM2 in the responses to environmental stresses and provided a potential target gene to enhance of the ability to hyperaccumulate metals.

An Efficient Agrobacterium-Mediated Genetic Transformation Method for Solanum betaceum Cav. Embryogenic Callus

Somatic embryogenesis in Solanum betaceum (tamarillo) has proven to be an effective model system for studying morphogenesis, since optimized plant regeneration protocols are available, and embryogenic competent cell lines can be induced from different explants. Nevertheless, an efficient genetic transformation system for embryogenic callus (EC) has not yet been implemented for this species. Here, an optimized faster protocol of genetic transformation using Agrobacterium tumefaciens is described for EC. The sensitivity of EC to three antibiotics was determined, and kanamycin proved to be the best selective agent for tamarillo callus. Two Agrobacterium strains, EHA105 and LBA4404, both harboring the p35SGUSINT plasmid, carrying the reporter gene for β-glucuronidase (gus) and the marker gene neomycin phosphotransferase (nptII), were used to test the efficiency of the process. To increase the success of the genetic transformation, a cold-shock treatment, coconut water, polyvinylpyrrolidone and an appropriate selection schedule based on antibiotic resistance were employed. The genetic transformation was evaluated by GUS assay and PCR-based techniques, and a 100% efficiency rate was confirmed in the kanamycin-resistant EC clumps. Genetic transformation with the EHA105 strain resulted in higher values for gus insertion in the genome. The protocol presented provides a useful tool for functional gene analysis and biotechnology approaches.

Current status and future prospects in cannabinoid production through in vitro culture and synthetic biology

For centuries, cannabis has been a rich source of fibrous, pharmaceutical, and recreational ingredients. Phytocannabinoids are the most important and well-known class of cannabis-derived secondary metabolites and display a broad range of health-promoting and psychoactive effects. The unique characteristics of phytocannabinoids (e.g., metabolite likeness, multi-target spectrum, and safety profile) have resulted in the development and approval of several cannabis-derived drugs. While most work has focused on the two main cannabinoids produced in the plant, over 150 unique cannabinoids have been identified. To meet the rapidly growing phytocannabinoid demand, particularly many of the minor cannabinoids found in low amounts in planta, biotechnology offers promising alternatives for biosynthesis through in vitro culture and heterologous systems. In recent years, the engineered production of phytocannabinoids has been obtained through synthetic biology both in vitro (cell suspension culture and hairy root culture) and heterologous systems. However, there are still several bottlenecks (e.g., the complexity of the cannabinoid biosynthetic pathway and optimizing the bioprocess), hampering biosynthesis and scaling up the biotechnological process. The current study reviews recent advances related to in vitro culture-mediated cannabinoid production. Additionally, an integrated overview of promising conventional approaches to cannabinoid production is presented. Progress toward cannabinoid production in heterologous systems and possible avenues for avoiding autotoxicity are also reviewed and highlighted. Machine learning is then introduced as a powerful tool to model, and optimize bioprocesses related to cannabinoid production. Finally, regulation and manipulation of the cannabinoid biosynthetic pathway using CRISPR- mediated metabolic engineering is discussed.

Optimization of Regeneration and Agrobacterium-Mediated Transformation Protocols for Bi and Multilocular Varieties of Brassica rapa

The regeneration of the high-yielding multilocular types has not been attempted, although successful regeneration and transformation in brassica have been done. Here, we report efficient regeneration and transformation protocols for two B. rapa genotypes; UAF11 and Toria. The B. rapa cv UAF11 is a multilocular, non-shattering, and high-yielding genotype, while Toria is the bilocular type. For UAF11 8 shoots and for Toria 7 shoots, explants were observed on MS supplemented with 3 mg/L BAP + 0.4 mg/L NAA + 0.01 mg/L GA₃ + 5 mg/L AgNO₃ + 0.75 mg/L Potassium Iodide (KI), MS salt supplemented with 1 mg/L IBA and 0.37 mg/L KI produced an equal number of roots (3) in UAF11 and Toria. For the establishment of transformation protocols, Agrobacterium-mediated floral dip transformation was attempted using different induction media, infection time, and flower stages. The induction medium III yielded a maximum of 7.2% transformants on half-opened flowers and 5.2% transformants on fully opened flowers in UAF11 and Toria, respectively, with 15 min of inoculation. This study would provide the basis for the improvement of tissue culture and transformation protocols in multilocular and bilocular Brassica genotypes.

Ectopic expression of a grapevine alkaline α-galactosidase seed imbibition protein VvSIP enhanced salinity tolerance in transgenic tobacco plants

Alpha-galactosidase seed imbibition protein (VvSIP) isolated from Vitis vinifera is up-regulated upon salt stress and mediates osmotic stress responses in a tolerant grapevine cultivar. So far, little is known about the putative role of this stress-responsive gene. In the present study, VvSIP function was investigated in model tobacco plants via Agrobacterium-mediated genetic transformation. Our results showed that overexpression of VvSIP exhibited increased tolerance to salinity at germination and late vegetative stage in transgenic Nicotiana benthamiana compared to the nontransgenic plants based on the measurement of the germination rate and biomass production. High salt concentrations of 200 and 400 mM NaCl in greenhouse-grown pot assay resulted in better relative water content, higher leaf osmotic potential, and leaf water potential in transgenic lines when compared to the wild-type (WT) plants. These physiological changes attributed to efficient osmotic adjustment improved plant performance and tolerance to salinity compared to the WT. Moreover, the VvSIP-expressing lines SIP1 and SIP2 showed elevated amounts of chlorophyll with lower malondialdehyde content indicating a reduced lipid peroxidation required to maintain membrane stability. When subjected to high salinity conditions, the transgenic tobacco VvSIP exhibited higher soluble sugar content, which may suggest an enhancement of the carbohydrate metabolism. Our findings indicate that the VvSIP is involved in plant salt tolerance by functioning as a positive regulator of osmotic adjustment and sugar metabolism, both of which are responsible for stress mitigation. Such a candidate gene is highly suitable to alleviate environmental stresses and thus could be a promising candidate for crop improvement.

Modeling and optimizing in vitro percentage and speed callus induction of carrot via Multilayer Perceptron-Single point discrete GA and radial basis function

Background

Callus induction is the first step in optimizing plant regeneration. Fit embryogenesis and shooting rely on callus induction. In addition, using artificial intelligence models in combination with an algorithm can be helpful in the optimization of in vitro culture. The present study aimed to evaluate the percentage and speed of callus induction optimization in carrot with a Multilayer Perceptron-Single point discrete genetic algorithm (GA).

Materials and methods

In this study, the outputs included callus induction percentage and speed, while inputs were different types and concentrations of plant growth regulator (0. 5, 0.2 mg/l 2,4-D, 0.3, 0.2, 0.5 mg/l BAP, 1, 0.2 mg/l Kin, and 2 mg/l NAA), different explants (shoot, root, leaf, and nodal), a different concentration compound of MS medium (1 × MS, 4× MS, and 8× MS) and time of sampling. The data were obtained in the laboratory, and multilayer perceptron (MLP) and radial basis function (RBF), two well-known ANNs, were employed to model. Then, GA was used for optimization, and sensitivity analysis was performed to indicate the inputs’ importance.

Results

The results showed that MLP had better prediction efficiency than RBF. Based on the results, R2 in training and testing data was 95 and 95% for the percentage of callus induction, while it was 94 and 95% for the speed of callus induction, respectively. In addition, a concentration compound of MS had high sensitivity, while times of sampling had low sensitivity. Based on the MLP-Single point discrete GA, the best results were obtained for shoot explants, 1× MS media, and 0.5 mg/l 2, 4-D + 0.5 mg/l BAP. Further, a non-significant difference was observed between the test result and predicted MLP.

Conclusions

Generally, MLP-Single point discrete GA is considered a potent tool for predicting treatment and fit model results used in plant tissue culture and selecting the best medium for callus induction.

Artificial neural network-based model to predict the effect of γ-aminobutyric acid on salinity and drought responsive morphological traits in pomegranate

Recently, γ-Aminobutyric acid (GABA) has been introduced as a treatment with high physiological activity induction to enhance the ability of plants against drought and salinity stress, which led to a decline in plant growth. Since changes in morphological traits to drought and salinity stress are influenced by multiple factors, advanced computational analysis has great potential for computing nonlinear and multivariate data. In this work, the effect of four input variables including GABA concentration, pomegranate cultivars, days of treatment, and drought and salinity stress evaluated to predict and modeling of morphological traits using artificial neural network (ANN) models including multilayer perceptron (MLP) and radial basis function (RBF). Image processing technique was used to measure the LLI, LWI, and LAI parameters. Among the ANNs applied, the MLP algorithm was chosen as the best model based on the highest accuracy. Furthermore, to predict and estimate the optimal values of input variables for achieving the best morphological parameters, the MLP algorithm was linked to a non-dominated sorting genetic algorithm-II (NSGA-II). Based on the results of MLP-NSGA-II, the best values of crown diameter (18.42 cm), plant height (151.82 cm), leaf length index (5.67 cm), leaf width index (1.76 cm), and leaf area index (13.82 cm) could be achieved with applying 10.57 mM GABA on ‘Atabaki’ cultivar under control (non-stress) condition after 20.8 days. The results of modeling and optimization can be helpful to predict the morphological responses to drought and salinity conditions.

Mathematical modeling and optimizing the in vitro shoot proliferation of wallflower using multilayer perceptron non-dominated sorting genetic algorithm-II (MLP-NSGAII)

Novel computational methods such as artificial neural networks (ANNs) can facilitate modeling and predicting results of tissue culture experiments and thereby decrease the number of experimental treatments and combinations. The objective of the current study is modeling and predicting in vitro shoot proliferation of Erysimum cheiri (L.) Crantz, which is an important bedding flower and medicinal plant. Its micropropagation has not been investigated before and as a case study multilayer perceptron- non-dominated sorting genetic algorithm-II (MLP-NSGAII) can be applied. MLP was used for modeling three outputs including shoots number (SN), shoots length (SL), and callus weight (CW) based on four variables including 6-benzylaminopurine (BAP), kinetin (Kin), 1-naphthalene acetic acid (NAA) and gibberellic acid (GA₃). The R² correlation values of 0.84, 0.99 and 0.93 between experimental and predicted data were obtained for SN, SL, and CW, respectively. These results proved the high accuracy of MLP model. Afterwards the model connected to Non-dominated Sorting Genetic Algorithm-II (NSGA-II) was used to optimize input variables for obtaining the best predicted outputs. The results of sensitivity analysis indicated that SN and CW were more sensitive to BA, followed by Kin, NAA and GA. For SL, more sensitivity was obtained for GA₃ than NAA. The validation experiment indicated that the difference between the validation data and MLP-NSGAII predicted data were negligible. Generally, MLP-NSGAII can be considered as a powerful method for modeling and optimizing in vitro studies.

AtQQS orphan gene and NtNF-YC4 boost protein accumulation and pest resistance in tobacco (Nicotiana tabacum)

Qua-Quine Starch (QQS), an orphan gene exclusively found in Arabidopsis thaliana, interacts with Nuclear Factor Y subunit C4 (NF-YC4) and regulates carbon and nitrogen allocation in different plant species. Several studies uncovered its potential in increasing total protein and resistance against pathogens/pests in Arabidopsis and soybean. However, it is still unclear if these attributes QQS offers are universal in all flowering plants. Here we studied AtQQS and Nicotiana tabacum NF-YC4's (NtNF-YC4) influence on starch/protein content and pest resistance in tobacco. Our results showed both AtQQS and NtNF-YC4 had a positive impact on the plant's total protein accumulation. Simultaneously, we have also observed reduced starch biosynthesis and increased resistance against common pests like whiteflies (Bemisia tabaci) and aphids (Myzus persicae) in tobacco plants expressing AtQQS or overexpressing NtNF-YC4. Real-time PCR also revealed increased NF-YC4 expression after aphid infestation in tobacco varieties with higher pest resistance but decreased/unchanged NF-YC4 expression in varieties susceptible to pests. Further analysis revealed that QQS expression and overexpression of NtNF-YC4 strongly repressed expression of genes such as sugar transporter SWEET10 and Flowering Locus T (FT), suggesting involvement of SWEET10 and FT in the QQS and NF-YC4 mediated carbon and nitrogen allocation in tobacco. Our data suggested that the activity of species-specific orphan genes may not be limited to the original species or its close relatives. Sequence alignment revealed the conserved sequence of the NF-YC4s in different plant species that may be responsible for the resulting shift in metabolism, pest resistance. Cis-acting DNA element analysis of NtNF-YC4 promoter region may outline potential mechanisms for these phenotypic changes.

Agrobacterium-Mediated Genetic Transformation of Embryogenic Callus in a Liriodendron Hybrid (L. Chinense × L. Tulipifera)

A highly efficient genetic transformation system of Liriodendron hybrid embryogenic calli through Agrobacterium-mediated genetic transformation was established and optimized. The Agrobacterium tumefaciens strain EHA105, harboring the plasmid pBI121, which contained the ß-glucuronidase (GUS) gene and neomycin phosphotransferase II (npt II) gene under the control of the CaMV35S promoter, was used for transformation. Embryogenic calli were used as the starting explant to study several factors affecting the Agrobacterium-mediated genetic transformation of the Liriodendron hybrid, including the effects of various media, selection by different Geneticin (G418) concentrations, pre-culture period, Agrobacterium optical density, infection duration, co-cultivation period, and delayed selection. Transformed embryogenic calli were obtained through selection on medium containing 90 mg L-1 G418. Plant regeneration was achieved and selected via somatic embryogenesis on medium containing 15 mg L-1 G418. The optimal conditions included a pre-culture time of 2 days, a co-culture time of 3 days, an optimal infection time of 10 min, and a delayed selection time of 7 days. These conditions, combined with an OD600 value of 0.6, remarkably enhanced the transformation rate. The results of GUS chemical tissue staining, polymerase chain reaction (PCR), and southern blot analysis demonstrated that the GUS gene was successfully expressed and integrated into the Liriodendron hybrid genome. A transformation efficiency of 60.7% was achieved for the regenerated callus clumps. Transgenic plantlets were obtained in 5 months, and the PCR analysis showed that 97.5% of plants from the tested G418-resistant lines were PCR positive. The study of the Liriodendron hybrid reported here will facilitate the insertion of functional genes into the Liriodendron hybrid via Agrobacterium-mediated transformation.

Genetic Dissection of CRISPR-Cas9 Mediated Inheritance of Independently Targeted Alleles in Tobacco α-1,3-Fucosyltransferase 1 and β-1,2-Xylosyltransferase 1 Loci

We determined the specificity of mutations induced by the CRISPR-Cas9 gene-editing system in tobacco (Nicotiana benthamiana) alleles and subsequent genetic stability. For this, we prepared 248 mutant plants using an Agrobacterium-delivered CRISPR-Cas9 system targeting α-1,3-fucosyltransferase 1 (FucT1) and β-1,2-xylosyltransferase1 (XylT1) genes, for which the mutation rates were 22.5% and 25%, respectively, with 20.5% for both loci. Individuals with wild-type (WT) alleles at the NbFucT1 locus in T0 were further segregated into chimeric progeny (37-54%) in the next generation, whereas homozygous T0 mutants tended to produce more (~70%) homozygotes than other bi-allelic and chimeric progenies in the T1 generation. Approximately 81.8% and 77.4% of the homozygous and bi-allelic mutations in T0 generation, respectively, were stably inherited in the next generation, and approximately 50% of the Cas9-free mutants were segregated in T2 generation. One homozygous mutant (Ta 161-1) with a +1 bp insertion in NbFucT1 and a -4 bp deletion in NbXylT1 was found to produce T2 progenies with the same alleles, indicating no activity of the integrated Cas9 irrespective of the insertion or deletion type. Our results provide empirical evidence regarding the genetic inheritance of alleles at CRISPR-targeted loci in tobacco transformants and indicate the potential factors contributing to further mutagenesis.

An Efficient Agrobacterium-Mediated Transformation Method for Hybrid Poplar 84K (Populus alba × P. glandulosa) Using Calli as Explants

A highly efficient Agrobacterium-mediated transformation method is needed for the molecular study of model tree species such as hybrid poplar 84K (Populus alba × P. glandulosa cv. ‘84K’). In this study, we report a callus-based transformation method that exhibits high efficiency and reproducibility. The optimized callus induction medium (CIM1) induced the development of calli from leaves with high efficiency, and multiple shoots were induced from calli growing on the optimized shoot induction medium (SIM1). Factors affecting the transformation frequency of calli were optimized as follows: Agrobacterium concentration sets at an OD₆₀₀ of 0.6, Agrobacterium infective suspension with an acetosyringone (AS) concentration of 100 µM, infection time of 15 min, cocultivation duration of 2 days and precultivation duration of 6 days. Using this method, transgenic plants are obtained within approximately 2 months with a transformation frequency greater than 50%. Polymerase chain reaction (PCR), reverse transcription-PCR (RT-PCR) and β-galactosidase (GUS) histochemical staining analyses confirmed the successful generation of stable transformants. Additionally, the calli from leaves were subcultured and used to obtain new explants; the high transformation efficiency was still maintained in subcultured calli after 6 cycles. This method provides a reference for developing effective transformation protocols for other poplar species.