Transgenic tomato lines expressing human lactoferrin show increased resistance to bacterial and fungal pathogens

Optimization of tissue culture and Cas9 transgene expression in tomato: A step towards CRISPR/Cas9-based genetic improvement

Tomato (Solanum lycopersicum L.) is an essential source of antioxidants and a prime candidate for bioengineering experiments. Many studies have aimed to improve tomatoes using CRISPR/Cas9 technology; however, the success rate is limited due to the lack of efficient regeneration and genetic modification techniques. Here, we report an efficient regeneration and transformation procedure focused on developing efficient Cas9 gene transgenic tomato plants using the Agrobacterium tumefaciens strain LBA4404 harbouring pCRISPR/Cas9TK2-NIC binary vector. We optimized the concentrations and combinations of growth hormones to promote direct shoot and root regeneration via hypocotyl explants. We found that MS medium 2.0 mg/l Zeatin (Zn) + 1.5 mg/l Indole -3- acetic acid (IAA) + 0.3 mg/l Benzyl amino purine (BAP) was preeminent for shoot regeneration medium, and 0.5 mg/l BAP+ 0.1 mg/l IAA was appropriate for root regeneration. Cas9 transgenes in the tomato genome of putative tomato plants were validated using various methods, including polymerase chain reaction (PCR), and confirmed via Southern blotting. The developed protocol showed improved regeneration and transformation efficiencies in tomatoes of 88 % and 54 %, respectively. In this study, we successfully established a gene delivery platform for tomatoes using the CRISPR/Cas9 system.

Lactoferrin and its role in biotechnological strategies for plant defense against pathogens

Agricultural crops are susceptible to many diseases caused by various pathogens, such as viruses, bacteria and fungi. This paper reviews the general principles of plant protection against pathogens, as well as the role of iron and antimicrobial peptide metabolism in plant immunity. The article highlights the principles of antibacterial, fungicidal and antiviral action of lactoferrin, a mammalian secretory glycoprotein, and lactoferrin peptides, and their role in protecting plants from phytopathogens. This review offers a comprehensive analysis and shows potential prospects of using the lactoferrin gene to enhance plant resistance to various phytopathogens, as well as the advantages of this biotechnological approach over existing methods of protecting plants against various diseases.

Plasmonic colloidal Au nanoparticles in DMSO: a facile synthesis and characterisation

We report a new pathway for the synthesis of plasmonic gold nanoparticles (Au NPs) in a bio-compatible medium. A modified room temperature approach based on the standard Turkevich synthesis, using sodium citrate as a reducing and stabilizing agent, results in a highly stable colloidal suspension of Au NPs in dimethyl sulfoxide (DMSO). The mean NP size of about 15 nm with a fairly low size distribution is revealed by scanning electron microscopy. The stability test through UV-vis absorption spectroscopy indicates no sign of aggregation for months. The Au NPs are also characterized by X-ray photoelectron, Raman scattering, and FTIR spectroscopies. The stabilisation mechanism of the Au NPs in DMSO is concluded to be similar to that of NPs synthesized in water. The Au NPs obtained in this work are applicable as SERS substrates, as proved by common analytes. In terms of bio-applications, they do not possess such side-effects as pronounced antibacterial activity, based on the tests performed on non-pathogenic Gram-positive or Gram-negative bacteria.

Highly efficient Agrobacterium-mediated transformation and plant regeneration system for genome engineering in tomato

Tomato (Solanum lycopersicum L.) is an important vegetable and nutritious crop plant worldwide. They are rich sources of several indispensable compounds such as lycopene, minerals, vitamins, carotenoids, essential amino acids, and bioactive polyphenols. Plant regeneration and Agrobacterium-mediated genetic transformation system from different explants in various genotypes of tomato are necessary for genetic improvement. Among diverse plant growth regulator (PGR) combinations and concentrations tested, Zeatin (ZEA) at 2.0 mg l-1 in combination with 0.1 mg l-1 indole-3-acetic acid (IAA) generated the most shoots/explant from the cotyledon of Arka Vikas (36.48 shoots/explant) and PED (24.68 shoots/explant), respectively. The hypocotyl explant produced 28.76 shoots/explant in Arka Vikas and 19.44 shoots/explant in PED. In contrast, leaf explant induced 23.54 shoots/explant in Arka Vikas and 17.64 shoots/explant in PED. The obtained multiple shoot buds from three explant types were elongated on a medium fortified with Gibberellic acid (GA3) (1.0 mg l-1), IAA (0.5 mg l-1), and ZEA (0.5 mg l-1) in both the cultivars. The rooting was observed on a medium amended with 0.5 mg l-1 indole 3-butyric acid (IBA). The transformation efficiency was significantly improved by optimizing the pre-culture of explants, co-cultivation duration, bacterial density and infection time, and acetosyringone concentration. The presence of transgenes in the plant genome was validated using different methods like histochemical GUS assay, Polymerase Chain Reaction (PCR), and Southern blotting. The transformation efficiency was 42.8% in PED and 64.6% in Arka Vikas. A highly repeatable plant regeneration protocol was established by manipulating various plant growth regulators (PGRs) in two tomato cultivars (Arka Vikas and PED). The Agrobacterium-mediated transformation method was optimized using different explants like cotyledon, hypocotyl, and leaf of two tomato genotypes. The present study could be favourable to transferring desirable traits and precise genome editing techniques to develop superior tomato genotypes.

Automatic and Reliable Leaf Disease Detection Using Deep Learning Techniques

Plants are a major source of food for the world population. Plant diseases contribute to production loss, which can be tackled with continuous monitoring. Manual plant disease monitoring is both laborious and error-prone. Early detection of plant diseases using computer vision and artificial intelligence (AI) can help to reduce the adverse effects of diseases and also overcome the shortcomings of continuous human monitoring. In this work, we propose the use of a deep learning architecture based on a recent convolutional neural network called EfficientNet on 18,161 plain and segmented tomato leaf images to classify tomato diseases. The performance of two segmentation models i.e., U-net and Modified U-net, for the segmentation of leaves is reported. The comparative performance of the models for binary classification (healthy and unhealthy leaves), six-class classification (healthy and various groups of diseased leaves), and ten-class classification (healthy and various types of unhealthy leaves) are also reported. The modified U-net segmentation model showed accuracy, IoU, and Dice score of 98.66%, 98.5%, and 98.73%, respectively, for the segmentation of leaf images. EfficientNet-B7 showed superior performance for the binary classification and six-class classification using segmented images with an accuracy of 99.95% and 99.12%, respectively. Finally, EfficientNet-B4 achieved an accuracy of 99.89% for ten-class classification using segmented images. It can be concluded that all the architectures performed better in classifying the diseases when trained with deeper networks on segmented images. The performance of each of the experimental studies reported in this work outperforms the existing literature.

Protein regulation strategies of the mouse spleen in response to Babesia microti infection

BACKGROUND

Babesia is a protozoan parasite that infects red blood cells in some vertebrates. Some species of Babesia can induce zoonoses and cause considerable harm. As the largest immune organ in mammals, the spleen plays an important role in defending against Babesia infection. When infected with Babesia, the spleen is seriously injured but still actively initiates immunomodulatory responses.

METHODS

To explore the molecular mechanisms underlying the immune regulation and self-repair of the spleen in response to infection, this study used data-independent acquisition (DIA) quantitative proteomics to analyse changes in expression levels of global proteins and in phosphorylation modification in spleen tissue after Babesia microti infection in mice.

RESULTS

After mice were infected with B. microti, their spleens were seriously damaged. Using bioinformatics methods to analyse dynamic changes in a large number of proteins, we found that the spleen still initiated immune responses to combat the infection, with immune-related proteins playing an important role, including cathepsin D (CTSD), interferon-induced protein 44 (IFI44), interleukin-2 enhancer-binding factor 2 (ILF2), interleukin enhancer-binding factor 3 (ILF3) and signal transducer and activator of transcription 5A (STAT5A). In addition, some proteins related to iron metabolism were also involved in the repair of the spleen after B. microti infection, including serotransferrin, lactoferrin, transferrin receptor protein 1 (TfR1) and glutamate-cysteine ligase (GCL). At the same time, the expression and phosphorylation of proteins related to the growth and development of the spleen also changed, including protein kinase C-δ (PKC-δ), mitogen-activated protein kinase (MAPK) 3/1, growth factor receptor-bound protein 2 (Grb2) and P21-activated kinase 2 (PAK2).

CONCLUSIONS

Immune-related proteins, iron metabolism-related proteins and growth and development-related proteins play an important role in the regulation of spleen injury and maintenance of homeostasis. This study provides an important basis for the diagnosis and treatment of babesiosis.