aBIOTECH最新文献

Phytic acid (PA) in grain seeds reduces the bioavailability of nutrient elements in monogastric animals, and an important objective for crop seed biofortification is to decrease the seed PA content. Here, we employed CRISPR/Cas9 to generate a PA mutant population targeting PA biosynthesis and transport genes, including two multi-drug-resistant protein 5 (MRP5) and three inositol pentose-phosphate kinases (IPK1). We characterized a variety of lines containing mutations on multiple IPK and MRP5 genes. The seed PA was more significantly decreased in higher-order mutant lines with multiplex mutations. However, such mutants also exhibited poor agronomic performance. In the population, we identified  two lines carrying single mutations in ipk1b and ipk1c, respectively. These mutants exhibited moderately reduced PA content, and regular agronomic performance compared to the wild type. Our study indicates that moderately decreasing PA by targeting single GmIPK1 genes, rather than multiplex mutagenesis toward ultra-low PA, is an optimal strategy for low-PA soybean with a minimal trade-off in yield performance.

Bakanae disease, caused by Fusarium fujikuroi, poses a significant threat to rice production and has been observed in most rice-growing regions. The disease symptoms caused by different pathogens may vary, including elongated and weak stems, slender and yellow leaves, and dwarfism, as example. Bakanae disease is likely to cause necrosis of diseased seedlings, and it may cause a large area of infection in the field through the transmission of conidia. Therefore, early disease surveillance plays a crucial role in securing rice production. Traditional monitoring methods are both time-consuming and labor-intensive and cannot be broadly applied. In this study, a combination of hyperspectral imaging technology and deep learning algorithms were used to achieve in situ detection of rice seedlings infected with bakanae disease. Phenotypic data were obtained on the 9th, 15th, and 21st day after rice infection to explore the physiological and biochemical performance, which helps to deepen the research on the disease mechanism. Hyperspectral data were obtained over these same periods of infection, and a deep learning model, named Rice Bakanae Disease-Visual Geometry Group (RBD-VGG), was established by leveraging hyperspectral imaging technology and deep learning algorithms. Based on this model, an average accuracy of 92.2% was achieved on the 21st day of infection. It also achieved an accuracy of 79.4% as early as the 9th day. Universal characteristic wavelengths were extracted to increase the feasibility of using portable spectral equipment for field surveillance. Collectively, the model offers an efficient and non-destructive surveillance methodology for monitoring bakanae disease, thereby providing an efficient avenue for disease prevention and control.

Rice (Oryza sativa) produces numerous diterpenoid phytoalexins that are important in defense against pathogens. Surprisingly, despite extensive previous investigations, a major group of such phytoalexins, the abietoryzins, were only recently reported. These aromatic abietanes are presumably derived from ent-miltiradiene, but such biosynthetic capacity has not yet been reported in O. sativa. While wild rice has been reported to contain such an enzyme, specifically ent-kaurene synthase-like 10 (KSL10), the only characterized ortholog from O. sativa (OsKSL10), specifically from the well-studied cultivar (cv.) Nipponbare, instead has been shown to make ent-sandaracopimaradiene, precursor to the oryzalexins. Notably, in many other cultivars, OsKSL10 is accompanied by a tandem duplicate, termed here OsKSL14. Biochemical characterization of OsKLS14 from cv. Kitaake demonstrates that this produces the expected abietoryzin precursor ent-miltiradiene. Strikingly, phylogenetic analysis of OsKSL10 across the rice pan-genome reveals that from cv. Nipponbare is an outlier, whereas the alleles from most other cultivars group with those from wild rice, suggesting that these also might produce ent-miltiradiene. Indeed, OsKSL10 from cv. Kitaake exhibits such activity as well, consistent with its production of abietoryzins but not oryzalexins. Similarly consistent with these results is the lack of abietoryzin production by cv. Nipponbare. Although their equivalent product outcome might suggest redundancy, OsKSL10 and OsKSL14 were observed to exhibit distinct expression patterns, indicating such differences may underlie retention of these duplicated genes. Regardless, the results reported here clarify abietoryzin biosynthesis and provide insight into the evolution of rice diterpenoid phytoalexins.

Loss-of-function mutants are fundamental resources for gene function studies. However, it is difficult to generate viable and heritable knockout mutants for essential genes. Here, we show that targeted editing of the C-terminal sequence of the embryo lethal gene MITOGEN-ACTIVATED PROTEIN KINASES 1 (OsMPK1) results in weak mutants. This C-terminal-edited osmpk1 mutants displayed severe developmental defects and altered disease resistance but generated tens of viable seeds that inherited the mutations. Using the same C-terminal editing approach, we also obtained viable mutants for a wall-associated protein kinase (Os07g0493200) and a leucine-rich repeat receptor-like protein kinase (Os01g0239700), while the null mutations of these genes were lethal. These data suggest that protein kinase activity could be reduced by introducing frameshift mutations adjacent to the C-terminus, which could generate valuable resources for gene function studies and tune protein kinase activity for signaling pathway engineering.

Basic helix-loop-helix (bHLH) transcription factors are widely distributed in eukaryotes, and in plants, they regulate many biological processes, such as cell differentiation, development, metabolism, and stress responses. Few studies have focused on the roles of bHLH transcription factors in regulating growth, development, and stress responses in maize (Zea mays), even though such information would greatly benefit maize breeding programs. In this study, we cloned the maize transcription factor gene ZmbHLH36 (Gene ID: 100193615, GRMZM2G008691). ZmbHLH36 possesses conserved domains characteristic of the bHLH family. RT-qPCR analysis revealed that ZmbHLH36 was expressed at the highest level in maize roots and exhibited different expression patterns under various abiotic stress conditions. Transgenic Arabidopsis (Arabidopsis thaliana) plants heterologously expressing ZmbHLH36 had significantly longer roots than the corresponding non-transgenic plants under 0.1 and 0.15 mol L⁻¹ NaCl treatment as well as 0.2 mol L⁻¹ mannitol treatment. Phenotypic analysis of soil-grown plants under stress showed that transgenic Arabidopsis plants harboring ZmbHLH36 exhibited significantly enhanced drought tolerance and salt tolerance compared to the corresponding non-transgenic plants. Malondialdehyde contents were lower and peroxidase activity was higher in ZmbHLH36-expressing Arabidopsis plants than in the corresponding non-transgenic plants. ZmbHLH36 localized to the nucleus when expressed in maize protoplasts. This study provides a systematic analysis of the effects of ZmbHLH36 on root growth, development, and stress responses in transgenic Arabidopsis, laying a foundation for further analysis of its roles and molecular mechanisms in maize.

Plants absorb light energy for photosynthesis via photosystem complexes in their chloroplasts. However, excess light can damage the photosystems and decrease photosynthetic output, thereby inhibiting plant growth and development. Plants have developed a series of light acclimation strategies that allow them to withstand high light. In the first line of defense against excess light, leaves and chloroplasts move away from the light and the plant accumulates compounds that filter and reflect the light. In the second line of defense, known as photoprotection, plants dissipate excess light energy through non-photochemical quenching, cyclic electron transport, photorespiration, and scavenging of excess reactive oxygen species. In the third line of defense, which occurs after photodamage, plants initiate a cycle of photosystem (mainly photosystem II) repair. In addition to being the site of photosynthesis, chloroplasts sense stress, especially light stress, and transduce the stress signal to the nucleus, where it modulates the expression of genes involved in the stress response. In this review, we discuss current progress in our understanding of the strategies and mechanisms employed by plants to withstand high light at the whole-plant, cellular, physiological, and molecular levels across the three lines of defense.

Genome editing holds great promise for the molecular breeding of plants, yet its application is hindered by the shortage of simple and effective means of delivering genome editing reagents into plants. Conventional plant transformation-based methods for delivery of genome editing reagents into plants often involve prolonged tissue culture, a labor-intensive and technically challenging process for many elite crop cultivars. In this review, we describe various virus-based methods that have been employed to deliver genome editing reagents, including components of the CRISPR/Cas machinery and donor DNA for precision editing in plants. We update the progress in these methods with recent successful examples of genome editing achieved through virus-based delivery in different plant species, highlight the advantages and limitations of these delivery approaches, and discuss the remaining challenges.

Root-associated microbiota profoundly affect crop health and productivity. Plants can selectively recruit beneficial microbes from the soil and actively balance microbe-triggered plant-growth promotion and stress tolerance enhancement. The cost associated with this is the root-mediated support of a certain number of specific microbes under nutrient limitation. Thus, it is important to consider the dynamic changes in microbial quantity when it comes to nutrient condition-induced root microbiome reassembly. Quantitative microbiome profiling (QMP) has recently emerged as a means to estimate the specific microbial load variation of a root microbiome (instead of the traditional approach quantifying relative microbial abundances) and data from the QMP approach can be more closely correlated with plant development and/or function. However, due to a lack of detailed-QMP data, how soil nutrient conditions affect quantitative changes in microbial assembly of the root-associated microbiome remains poorly understood. A recent study quantified the dynamics of the soybean root microbiome, under unbalanced fertilization, using QMP and provided data on the use of specific synthetic communities (SynComs) for sustaining crop productivity. In this editorial, we explore potential opportunities for utilizing QMP to decode the microbiome for sustainable agriculture.