Investigating Phragmites australis response to copper exposure using physiologic, Fourier Transform Infrared and metabolomic approaches

Mitochondrial Genome Insights into Evolution and Gene Regulation in Phragmites australis

As a globally distributed perennial Gramineae, Phragmites australis can adapt to harsh ecological environments and has significant economic and environmental values. Here, we performed a complete assembly and annotation of the mitogenome of P. australis using genomic data from the PacBio and BGI platforms. The P. australis mitogenome is a multibranched structure of 501,134 bp, divided into two circular chromosomes of 325,493 bp and 175,641 bp, respectively. A sequence-simplified succinate dehydrogenase 4 gene was identified in this mitogenome, which is often translocated to the nuclear genome in the mitogenomes of gramineous species. We also identified tissue-specific mitochondrial differentially expressed genes using RNAseq data, providing new insights into understanding energy allocation and gene regulatory strategies in the long-term adaptive evolution of P. australis mitochondria. In addition, we studied the mitogenome features of P. australis in more detail, including repetitive sequences, gene Ka/Ks analyses, codon preferences, intracellular gene transfer, RNA editing, and multispecies phylogenetic analyses. Our results provide an essential molecular resource for understanding the genetic characterisation of the mitogenome of P. australis and provide a research basis for population genetics and species evolution in Arundiaceae.

Phytobial remediation advances and application of omics and artificial intelligence: a review

Industrialization and urbanization increased the use of chemicals in agriculture, vehicular emissions, etc., and spoiled all environmental sectors. It causes various problems among living beings at multiple levels and concentrations. Phytoremediation and microbial association are emerging as a potential method for removing heavy metals and other contaminants from soil. The treatment uses plant physiology and metabolism to remove or clean up various soil contaminants efficiently. In recent years, omics and artificial intelligence have been seen as powerful techniques for phytobial remediation. Recently, AI and modeling are used to analyze large data generated by omics technologies. Machine learning algorithms can be used to develop predictive models that can help guide the selection of the most appropriate plant and plant growth-promoting rhizobacteria combination that is most effective at remediation. In this review, emphasis is given to the phytoremediation techniques being explored worldwide in soil contamination.

DAST: A Domain-Adaptive Learning Combining Spatio-Temporal Dynamic Attention for Electroencephalography Emotion Recognition

Multimodal emotion recognition with EEG-based have become mainstream in affective computing. However, previous studies mainly focus on perceived emotions (including posture, speech or face expression et al.) of different subjects, while the lack of research on induced emotions (including video or music et al.) limited the development of two-ways emotions. To solve this problem, we propose a multimodal domain adaptive method based on EEG and music called the DAST, which uses spatio-temporal adaptive attention (STA-attention) to globally model the EEG and maps all embeddings dynamically into high-dimensionally space by adaptive space encoder (ASE). Then, adversarial training is performed with domain discriminator and ASE to learn invariant emotion representations. Furthermore, we conduct extensive experiments on the DEAP dataset, and the results show that our method can further explore the relationship between induced and perceived emotions, and provide a reliable reference for exploring the potential correlation between EEG and music stimulation.

Transcriptomics, proteomics, and metabolomics interventions prompt crop improvement against metal(loid) toxicity

The escalating challenges posed by metal(loid) toxicity in agricultural ecosystems, exacerbated by rapid climate change and anthropogenic pressures, demand urgent attention. Soil contamination is a critical issue because it significantly impacts crop productivity. The widespread threat of metal(loid) toxicity can jeopardize global food security due to contaminated food supplies and pose environmental risks, contributing to soil and water pollution and thus impacting the whole ecosystem. In this context, plants have evolved complex mechanisms to combat metal(loid) stress. Amid the array of innovative approaches, omics, notably transcriptomics, proteomics, and metabolomics, have emerged as transformative tools, shedding light on the genes, proteins, and key metabolites involved in metal(loid) stress responses and tolerance mechanisms. These identified candidates hold promise for developing high-yielding crops with desirable agronomic traits. Computational biology tools like bioinformatics, biological databases, and analytical pipelines support these omics approaches by harnessing diverse information and facilitating the mapping of genotype-to-phenotype relationships under stress conditions. This review explores: (1) the multifaceted strategies that plants use to adapt to metal(loid) toxicity in their environment; (2) the latest findings in metal(loid)-mediated transcriptomics, proteomics, and metabolomics studies across various plant species; (3) the integration of omics data with artificial intelligence and high-throughput phenotyping; (4) the latest bioinformatics databases, tools and pipelines for single and/or multi-omics data integration; (5) the latest insights into stress adaptations and tolerance mechanisms for future outlooks; and (6) the capacity of omics advances for creating sustainable and resilient crop plants that can thrive in metal(loid)-contaminated environments.

Metabolomics reveals the response of hydroprimed maize to mitigate the impact of soil salinization

Soil salinization is a major environmental stressor hindering global crop production. Hydropriming has emerged as a promising approach to reduce salt stress and enhance crop yields on salinized land. However, a better mechanisitic understanding is required to improve salt stress tolerance. We used a biochemical and metabolomics approach to study the effect of salt stress of hydroprimed maize to identify the types and variation of differentially accumulated metabolites. Here we show that hydropriming significantly increased catalase (CAT) activity, soluble sugar and proline content, decreased superoxide dismutase (SOD) activity and peroxide (H₂O₂) content. Conversely, hydropriming had no significant effect on POD activity, soluble protein and MDA content under salt stress. The Metabolite analysis indicated that salt stress significantly increased the content of 1278 metabolites and decreased the content of 1044 metabolites. Ethisterone (progesterone) was the most important metabolite produced in the roots of unprimed samples in response to salt s tress. Pathway enrichment analysis indicated that flavone and flavonol biosynthesis, which relate to scavenging reactive oxygen species (ROS), was the most significant metabolic pathway related to salt stress. Hydropriming significantly increased the content of 873 metabolites and significantly decreased the content of 1313 metabolites. 5-Methyltetrahydrofolate, a methyl donor for methionine, was the most important metabolite produced in the roots of hydroprimed samples in response to salt stress. Plant growth regulator, such as melatonin, gibberellin A8, estrone, abscisic acid and brassinolide involved in both treatment. Our results not only verify the roles of key metabolites in resisting salt stress, but also further evidence that flavone and flavonol biosynthesis and plant growth regulator relate to salt tolerance.

Photosynthesis-related physiology and metabolomics responses of Polygonum lapathifolium in contrasting manganese environments

Manganese (Mn) plays an essential role in plant growth; however, excessive Mn is toxic to plants. Polygonum lapathifolium Linn. was tested as a novel Mn-hyperaccumulating species in our previous study, but the underlying mechanisms of this hyperaccumulation are poorly understood. A hydroponic experiment with (8mmolL-1 ) and without additional Mn (CK) was established to explore the possible mechanisms through the effects on photosynthesis-related physiological characteristics and metabolomics. The results showed that additional Mn increased plant biomass, photosynthesis, and stomatal conductance related to increases in the effective photochemical quantum yield of photosystem II and relative electron transport rate (P <0.05). The results from liquid chromatography-mass spectrometry revealed 56 metabolites differentially accumulated between the plants composing these two groups. Metabolites were enriched in 20 metabolic pathways at three levels (environmental information processing, genetic information processing, and metabolism), of which five metabolic pathways were associated with significant or extremely significant changes (P <0.05). These five enriched pathways were ABC transporters (environmental information processing), aminoacyl-tRNA biosynthesis (genetic information processing), biosynthesis of amino acids , d -arginine and d -ornithine metabolism , and arginine biosynthesis (metabolism). Flavonoids may play a key role in Mn tolerance, as they accumulated more than 490-fold, and the relationship between flavonoids and Mn tolerance needs to be studied in the future.