aBIOTECH最新文献

Tobacco (Nicotiana tabacum) plants synthesize the psychoactive pyridine alkaloid nicotine, which has sparked growing interest in reducing nicotine levels through genome editing aiming at inactivating key biosynthetic genes. Although stable transformation-mediated genome editing is effective in tobacco, its polyploid nature complicates the complete knockout of genes and the segregation of transgenes from edited plants. In this study, we developed a non-transgenic genome editing method in tobacco by delivering the CRISPR/Cas machinery via an engineered negative-strand RNA rhabdovirus vector, followed by the regeneration of mutant plants through tissue culture. Using this method, we targeted six berberine bridge enzyme-like protein (BBL) family genes for mutagenesis, which are implicated in the last steps of pyridine alkaloid biosynthesis, in the commercial tobacco cultivar Hongda. We generated a panel of 16 mutant lines that were homozygous for mutations in various combinations of BBL genes. Alkaloid profiling revealed that lines homozygous for BBLa and BBLb mutations exhibited drastically reduced nicotine levels, while other BBL members played a minor role in nicotine synthesis. The decline of nicotine content in these lines was accompanied by reductions in anatabine and cotinine levels but increases in nornicotine and its derivative myosmine. Preliminary agronomic evaluation identified two low-nicotine lines with growth phenotypes comparable to those of wild-type plants under greenhouse and field conditions. Our work provides potentially valuable genetic materials for breeding low-nicotine tobacco and enhances our understanding of alkaloid biosynthesis.

Tomato (Solanum lycopersicum) and potato (Solanum tuberosum), two integral crops within the nightshade family, are crucial sources of nutrients and serve as staple foods worldwide. Molecular genetic studies have significantly advanced our understanding of their domestication, evolution, and the establishment of key agronomic traits. Recent studies have revealed that epigenetic modifications act as “molecular switches”, crucially regulating phenotypic variations essential for traits such as fruit ripening in tomatoes and tuberization in potatoes. This review summarizes the latest findings on the regulatory mechanisms of epigenetic modifications in these crops and discusses the integration of biotechnology and epigenomics to enhance breeding strategies. By highlighting the role of epigenetic control in augmenting crop yield and adaptation, we underscores its potential to address the challenges posed by a growing global population as well as changing climate.

The effect of fungicides on the plant-rhizosphere microbiome is a subject of ongoing debate, but whether any alteration in the rhizosphere microbiome could affect plant health is an issue that has not been thoroughly investigated. To address this deficiency, we analyzed the rhizosphere microbiome of wilt disease—resistant and disease-susceptible cucumber cultivars to determine whether (and which) plant-associated microorganisms have a role in disease resistance. We further assessed whether the fungicides thiophanate-methyl and carbendazim affect the rhizosphere microbiome, which may contribute to the plant’s immune response. Based on results acquired with both radicle-inoculation and soil-inoculation methods, cultivars Longyuanxiuchun (LYXC) and Shuyan2 (SY2) were identified as being disease resistant, whereas Zhongnong6 (ZN6) and Zhongnong38 (ZN38) were susceptible. The microbiome structure differed substantially between the resistant and susceptible plants, with LYXC and SY2 each having a significantly greater Shannon index than Zhongnong38. These results revealed that the disease-resistant cucumber cultivars recruited more beneficial bacteria, i.e., Bacillus, in their rhizosphere soil; as such, Bacillus was identified as a keystone genus in the microbial co-occurrence network. Thus, the presence of Bacillus may help cucumbers defend against fungal pathogens within the rhizosphere. Bacillus subtilis strain LD15, which was isolated from LYXC rhizosphere soil, could suppress pathogen growth, in vitro, and reduce disease severity in pot assays. Moreover, evidence also confirmed the accumulation of LD1 in the rhizosphere soil of resistant cucumber cultivars. For LYXC, application of thiophanate-methyl or carbendazim altered the microbiome structure, decreased bacterial diversity, and reduced the abundance of Bacillus species. Finally, pot assays verified that fungicide application decreased the proportion of LD15 in rhizosphere soil. From a microbial perspective, thiophanate-methyl and carbendazim may weaken the rhizobacteria-mediated defense response of cucumbers against cucumber Fusarium wilt disease. Our findings reveal a role for the rhizosphere microbiome in protecting plants from pathogens and constitute a reference for assessing the ecotoxicological risk of pesticides to non-target soil microorganisms.

Sorghum, the fifth largest global cereal crop, comprises various types, such as grain, sweet, forage, and biomass sorghum, delineated by their designated end uses. Among these, sweet sorghum (Sorghum bicolor (L.) Moench) stands out for its unique versatility, exceptional abiotic stress tolerance and large biomass serving the multi-purpose of high-sugar forage, syrup, and biofuel production. Despite its significance, functional genomic research and biotechnological breeding in sweet sorghum are still in nascent stages, necessitating more efficient genetic transformation and genome-editing techniques. This study unveils Gaoliangzhe (GZ), an elite sweet sorghum variety for heightened resistance to salinity and drought. Through the establishment of an Agrobacterium tumefaciens‐mediated genetic transformation and CRISPR/Cas9-based genome-editing system in GZ, a breakthrough is achieved. Using genome-editing technology, we first produced a fragrant sweet sorghum line by targeting the BETAINE ALDEHYDE DEHYDROGENASE 2 (SbBADH2) gene. Our results establish a strong foundation for further functional genomic research and biotechnological breeding of sweet-sorghum varieties.

CRISPR/Cas-based genome editing has been extensively employed in the breeding and genetic improvement of trees, yet precise editing remains challenging in these species. Prime editing (PE), a revolutionary technology for precise editing, allows for arbitrary base substitutions and the insertion/deletion of small fragments. In this study, we focused on the model tree poplar 84K (Populus alba × P. glandulosa). We used the 2 × 35S promoter to express a fusion protein of spCas9 nickase (nCas9) and engineered Moloney murine leukemia virus (MMLV), and the Arabidopsis thaliana AtU6 promoter to express an engineered PE guide RNA (epegRNA) and Nick gRNA, pioneering the establishment of the Prime Editor 3 (PE3) system in dicot poplar. Single-base substitutions, multiple-base substitutions, and small-fragment insertions/deletions were edited into three endogenous target genes. The desired edits were identified in hygromycin-resistant (transformed) calli at seven out of nine target sites, with an average editing efficiency ranging from 0.1 to 3.6%. Furthermore, stable T₀ plants contained the desired edits at four out of nine targets, with editing efficiencies ranging from 3.6 to 22.2%. Establishment of the PE3 system provides a powerful tool for the precise modification of the poplar genome.

Accurate taxonomic classification is essential to understanding microbial diversity and function through metagenomic sequencing. However, this task is complicated by the vast variety of microbial genomes and the computational limitations of bioinformatics tools. The aim of this study was to evaluate the impact of reference database selection and confidence score (CS) settings on the performance of Kraken2, a widely used k-mer-based metagenomic classifier. In this study, we generated simulated metagenomic datasets to systematically evaluate how the choice of reference databases, from the compact Minikraken v1 to the expansive nt- and GTDB r202, and different CS (from 0 to 1.0) affect the key performance metrics of Kraken2. These metrics include classification rate, precision, recall, F1 score, and accuracy of true versus calculated bacterial abundance estimation. Our results show that higher CS, which increases the rigor of taxonomic classification by requiring greater k-mer agreement, generally decreases the classification rate. This effect is particularly pronounced for smaller databases such as Minikraken and Standard-16, where no reads could be classified when the CS was above 0.4. In contrast, for larger databases such as Standard, nt and GTDB r202, precision and F1 scores improved significantly with increasing CS, highlighting their robustness to stringent conditions. Recovery rates were mostly stable, indicating consistent detection of species under different CS settings. Crucially, the results show that a comprehensive reference database combined with a moderate CS (0.2 or 0.4) significantly improves classification accuracy and sensitivity. This finding underscores the need for careful selection of database and CS parameters tailored to specific scientific questions and available computational resources to optimize the results of metagenomic analyses.

Mosses, particularly desiccation-tolerant (DT) species, are important model organisms for studying genes involved in plant development and stress resistance. The lack of a simple and efficient stable moss transformation system has hindered progress in deciphering the genetic mechanisms underlying traits of interest in these organisms. Here, we present an Agrobacterium tumefaciens-mediated transformation system for DT mosses that uses Agrobacterium strain EHA105 harboring the binary vector pCAMBIA1301-GUS. This system achieved transformation efficiencies of 74% and 81% in Physcomitrium patens and Bryum argenteum protonemata, respectively, without the need for culture and callus formation prior to regeneration. We detected GUS enzyme activity in the regenerated transgenic moss via histochemical staining. Southern blot, PCR, and RT-qPCR analyses confirmed the presence of the GUS gene. In addition, we successfully used this system to transform wild DT Syntrichia caninervis. Furthermore, P. patens and B. argenteum transformed using this system with the stress resistance gene EsDREB from the desert plant Eremosparton songoricum (Litv.) exhibited improved salt tolerance. We thus present an efficient tool for the genetic analysis of DT moss species, paving the way for the development of stress-resistant crop cultivars.

A regulon refers to a group of genes regulated by a transcription factor binding to regulatory motifs to achieve specific biological functions. To infer tissue-specific gene regulons in Arabidopsis, we developed a novel pipeline named InferReg. InferReg utilizes a gene expression matrix that includes 3400 Arabidopsis transcriptomes to make initial predictions about the regulatory relationships between transcription factors (TFs) and target genes (TGs) using co-expression patterns. It further improves these anticipated interactions by integrating TF binding site enrichment analysis to eliminate false positives that are only supported by expression data. InferReg further trained a graph convolutional network with 133 transcription factors, supported by ChIP-seq, as positive samples, to learn the regulatory logic between TFs and TGs to improve the accuracy of the regulatory network. To evaluate the functionality of InferReg, we utilized it to discover tissue-specific regulons in 5 Arabidopsis tissues: flower, leaf, root, seed, and seedling. We ranked the activities of regulons for each tissue based on reliability using Borda ranking and compared them with existing databases. The results demonstrated that InferReg not only identified known tissue-specific regulons but also discovered new ones. By applying InferReg to rice expression data, we were able to identify rice tissue-specific regulons, showing that our approach can be applied more broadly. We used InferReg to successfully identify important regulons in various tissues of Arabidopsis and Oryza, which has improved our understanding of tissue-specific regulations and the roles of regulons in tissue differentiation and development.