Proteomics has become one of the most dynamic hotspots in biomedical research, botany, microbiology, and other fields in the 21st century. Its theories and methods are flourishing in the field of botany, permeating into various areas such as plant genetics, plant physiology, plant developmental biology, plant ecology, plant symbiosis, and plant pathology. It has injected new vitality into research in related agricultural biological science fields such as agronomy, forestry, animal husbandry, and aquaculture. In the field of agricultural production, proteomics has been widely applied in research on crop genetic breeding, crop responses to environmental stress, improvement of crop quality, and interactions between crops and microorganisms.
In the natural environment, various abiotic and biotic factors can adversely affect the growth and development of plants, and in severe cases, lead to plant death. Plants have strong response mechanisms to these stressors, adapting to unfavorable environmental conditions through a series of responses at the cellular and physiological levels. Applying proteomic techniques to study changes in the types and expression levels of plant proteins under stress conditions can help people understand the mechanisms of damage caused by stress factors and the adaptation mechanisms of plants from a holistic and dynamic perspective at the protein level.
Case 1. Understanding Copper Stress Response in European Rapeseed [1]
Heavy metal pollution is rapidly increasing, bringing about numerous serious environmental issues. Excessive heavy metals not only reduce soil fertility and crop yields but also pose a threat to human health through the food chain. The essential micronutrient copper (Cu) plays a crucial role in the extensive biological activities and redox reactions in plants. However, an excess of copper in plants can lead to phytotoxicity, potentially damaging various physiological processes. Citric acid (CA), a low molecular weight organic acid, serves as an intermediate in the tricarboxylic acid (TCA) cycle and plays a significant role in enhancing the bioavailability and removal efficiency of heavy metals in polluted soils. The protective effect of CA against metal-induced oxidative stress has also captured the attention of scientists, aiming to increase the activity of key enzymes in the antioxidant defense system.
Brassica rapa, a type of kale, can accumulate a large amount of heavy metals in its stems and is well-suited for removing heavy metals from soil. Additionally, the application of exogenous CA promotes the absorption and translocation of metals from roots to stems, facilitating the uptake of metals, including copper, by plants and inducing tolerance to oxidative stress. However, the response mechanisms of European rapeseed to copper stress and its interaction with exogenous CA, especially at the protein level, are unknown. This study employed a label-free quantitative proteomics approach using the LTQ Orbitrap mass spectrometer to analyze the differential abundance proteins (DAP) in European rapeseed seedlings in response to copper.
The differential abundance curves of quantified proteins are displayed in the heatmap for comparing DAP among different sample groups (Figure 1). The differential protein abundance is shown in the heatmap based on the fold change ratio normalized by the exponentially modified protein abundance index (emPAI). In comparison to the control samples, 426 differentially abundant proteins were detected in all treatments, and their abundance differences are illustrated in the heatmap (Figure 1).
Figure 1. Heatmap analysis of 426 differentially abundant proteins
Using the LTQ Orbitrap mass spectrometer, a total of 6345 proteins were identified in the leaves of all treatments at a 95% confidence level. Among these proteins, 1140, 1086, 1200, 990, 853, and 1076 proteins were identified in the control, CA, Cu 25 μM, CA + Cu 25 μM, Cu 50 μM, and CA + Cu 50 μM samples of European rapeseed, respectively. Generally, 552 proteins were commonly identified across all treatments.
Comparing the control with CA, 211 differentially abundant proteins (DAP) were identified, including 13 upregulated proteins and 198 downregulated proteins. In the comparison between the control and Cu 25 μM, 142 DAP were identified, comprising 2 upregulated proteins and 113 downregulated proteins. For the control versus CA + Cu 25 μM, 131 DAP were identified, including 123 upregulated proteins and 8 downregulated proteins. In the control versus Cu 50 μM comparison, 76 DAP were identified, consisting of 54 upregulated proteins and 22 downregulated proteins. The control versus CA + Cu 50 μM comparison revealed 111 DAP, with 37 upregulated proteins and 74 downregulated proteins (Figure 2).
To infer overlapping and unique proteins in different treatment groups, a Venn diagram analysis was performed for DAP representing upregulated and downregulated proteins. It is noteworthy that 7 upregulated DAP were commonly detected in the Cu 25, CA + Cu 25, Cu 50, and CA + Cu 50 groups, while 105 downregulated DAP were found between the CA and Cu 25 groups. The higher number of upregulated proteins (98 DAP) in the CA + Cu 25 samples indicates an increased abundance of proteins involved in responding to copper stress mediated by CA.
Figure 2. Identification and statistical analysis of Differentially Abundant Proteins (DAPs) in different treatment groups
DAVID functional annotation analysis indicates that the most enriched Gene Ontology (GO) terms can be assigned to the identified proteins (Figure 3). For the category of biological processes, the majority of identified proteins are involved in translation (131 proteins), response to metal ions (114 proteins), and glycolysis (95 proteins). Regarding cellular components, chloroplasts (440 proteins), cytoplasm (341 proteins), and the nucleus (259 proteins) exhibit predominant GO terms. ATP binding (146 proteins), structural constituent of ribosome (128 proteins), and protein binding (120 proteins) represent the most enriched groups in the molecular function category. GO annotation analysis suggests that these enriched GO terms play a crucial role in the plant's response to copper stress.
Figure 3: GO annotations of all identified proteins in different treatment groups of rapeseed
To gain a deeper understanding of metabolic changes, the Kyoto Encyclopedia of Genes and Genomes (KEGG) database (http://www.kegg.jp/; access date, October 6, 2020) was utilized. Potential metabolic pathways were constructed based on the differentially abundant proteins (DAP) affected by copper stress in the leaves of European rapeseed seedlings. The most enriched KEGG pathways in each sample group are depicted in Figure 4.
Figure 4. KEGG metabolic pathway analysis of differentially abundant proteins (daps) in different treatment groups of rapeseed
In this study, a label-free proteomics approach identified a total of 6345 proteins in the leaves of differentially treated rapeseed. Among them, 426 proteins showed differential expression across the treatment groups. Gene Ontology (GO) and KEGG pathway analyses indicated that the majority of differentially abundant proteins are involved in energy and carbohydrate metabolism, photosynthesis, protein metabolism, stress and defense, metal detoxification, and cell wall remodeling. The results of this study suggest that the downregulation of chlorophyll biosynthesis proteins involved in photosynthesis is consistent with the decrease in chlorophyll content. These findings provide potential molecular mechanisms for copper stress tolerance and open up a new avenue for accelerating plant copper handling through the exogenous application of citric acid (CA).
Reference
- Raza, Ali, et al. "Integrated analysis of metabolome and transcriptome reveals insights for cold tolerance in rapeseed (Brassica napus L.)." Frontiers in Plant Science 12 (2021): 721681.
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