基于非靶向代谢组学分析丛枝病感病与未感病苦豆子代谢物的差异

doi:10.11686/cyxb2024258

摘要/Abstract

摘要：

植原体会导致寄主植物黄化、顶枯、丛枝、簇生、小叶、矮化、花变叶等症状，迄今我国植原体病害有100多种，包括重要的经济作物、中草药及林木等病害。由植原体引起的苦豆子丛枝病导致寄主生长被抑制、种子绝收、产量降低等，对我国苦豆子相关产业带来了潜在的威胁。以植原体侵染感病苦豆子、健康苦豆子为研究对象，利用形态学、分子生物学、非靶向代谢组学分析苦豆子丛枝病病原及病原侵染对苦豆子代谢物的影响。结果表明引起苦豆子丛枝病的病原菌为16Sr V-B亚组成员；病原感染显著改变了苦豆子代谢物，差异代谢物主要注释到环境信息处理、遗传信息处理和新陈代谢三大功能，其中新陈代谢占92.38%，通过KEGG通路气泡图分析发现卟啉和叶绿素代谢及苯丙氨酸、酪氨酸和色氨酸的生物合成通路具有显著差异，初步推测病原菌的侵染主要通过寄主代谢物的变化引起寄主植物的感病，其中以上2个通路的变化对苦豆子丛枝病的发生具有重要的作用，即病原菌的侵染降低寄主光合能力从而引起营养匮乏及抗性降低引起感病。

关键词: 苦豆子, 丛枝病, 非靶向代谢组学, KEGG分析

Abstract:

Phytoplasma is a bacterial pathogen that induces a range of symptoms in host plants， including yellowing， apical necrosis， witches’ broom， phyllody， dwarfism， and floral changes. In China， more than 100 types of phytoplasma diseases have been identified that affect important economic crops， traditional Chinese medicinal herbs， and forestry. Witches’ broom disease， caused by phytoplasma infection in Sophora alopecuroides， inhibits growth， causes seed production failure， and reduces yield， posing a potential threat to industries that utilize S. alopecuroides in China. This study focused on the impact of phytoplasma infection on S. alopecuroides metabolites by comparing infected and healthy plants using morphological， molecular biological， and untargeted metabolomic analyses. Our results indicate that the phytoplasma strain causing witches’ broom disease in S. alopecuroides belongs to the 16Sr V-B subgroup. Infection significantly altered the metabolite profile of S. alopecuroides， with differentially annotated metabolites primarily associated with environmental information processing， genetic information processing， and metabolism， with the latter constituting 92.38% of total observed metabolite changes. KEGG pathway analysis revealed significant differences in the porphyrin and chlorophyll metabolism pathways as well as in the biosynthesis of phenylalanine， tyrosine， and tryptophan. It is speculated that phytoplasma infection may induce disease symptoms in the host plant primarily through changes in host metabolites. Alterations in these two pathways play a crucial role in the occurrence of witches’ broom disease in S. alopecuroides， suggesting that infection reduces the photosynthetic capacity of the host， leading to nutrient deficiency and decreased resistance， which in turn aids disease progression.

Key words: Sophora alopecuroides, witches’ broom disease, non-targeted metabolomics, KEGG analysis

赛牙热木·哈力甫, 杨莉, 李冠宏, 朱永琪, 李东. 基于非靶向代谢组学分析丛枝病感病与未感病苦豆子代谢物的差异[J]. 草业学报, 2025, 34(5): 105-117.

Halifu SAIYAREMU, Li YANG, Guan-hong LI, Yong-qi ZHU, Dong LI. Analysis of metabolite differences in Sophora alopecuroides infected and non-infected by witches’ broom disease based on non-targeted metabolomics[J]. Acta Prataculturae Sinica, 2025, 34(5): 105-117.

图/表 12

表1 色谱梯度洗脱程序

Table 1 Gradient elution program in chromatography

时间Time （min）	A （%）	B （%）
0	98	2
1.5	98	2
3.0	15	85
10.0	0	100
10.1	98	2
11.0	98	2
12.0	98	2

图1 病原菌的鉴定

Fig.1 Identification of pathogenic bacteria

图2 不同组样品的数据质控分析A和B分别为正离子和负离子模式下QC样本之间的Pearson相关性分析；C和D分别为正离子和负离子模式下不同样本之间的主成分分析。A and B represent the Pearson correlation analysis among QC samples in positive ion and negative ion modes， respectively； C and D represent the PCA among different samples in positive ion and negative ion modes， respectively.

Fig.2 Data audit analysis of different samples

图3 不同组样品的PCA分析A和B分别为正离子和负离子模式下健康样品和感病样品的PCA分析。A and B represent the PCA analysis between CRA and CRB samples in positive ion and negative ion modes， respectively.

Fig.3 PCA analysis of different samples

图4 不同组样品的PLS-DA分析A和B分别为正离子和负离子模式下健康样品和感病样品的PLC-DA分析。A and B represent PLC-DA analysis between CRA and CRB samples in positive ion and negative ion modes， respectively.

Fig.4 PLS-DA analysis of different samples

表2 差异代谢物筛选结果

Table 2 Differential metabolite screening results

模式

Pattern

总代谢物

Total metabolites

差异代谢物

Differential metabolites

上调数

Up regulation

下调数

Down regulation

图5 差异代谢物聚类热图A和B分别为正离子和负离子模式下健康样品和感病样品的差异代谢物聚类热图。A and B represent heat map analysis between CRA and CRB samples in positive ion and negative ion modes， respectively.

Fig.5 Heat map of differential metabolite clustering

图6 KEGG通路分析

Fig.6 KEGG pathway analysis

图7 KEGG通路气泡图

Fig.7 KEGG pathway bubble analysis

图8 卟啉和叶绿素部分代谢通路红色字体代表该代谢物上调；方框中数字代表酶的EC编号。The red font indicates that the metabolite is upregulated； The numbers in the box represent the enzyme commission number. 下同The same below.

Fig.8 Porphyrin and chlorophyll metabolic pathways

表3 部分代谢通路中代谢物的变化

Table 3 Metabolite changes in some metabolic pathways

代谢物Metabolite	ID	健康植株CRA	感病植株CRB	FC=CRB/CRA
卟啉原Porphobilinogen	Com_11857_neg	26533130.21	64482547.45	2.43
原卟啉Ⅸ Protoporphyrin Ⅸ	Com_2543_neg	3804321.43	45306217.92	11.90
胆红Bilirubin	Com_6145_neg	19186067.00	161795366.00	8.40
L-谷氨酸L-glutamic acid	Com_12661_neg	175614518.60	17230857.15	0.10
D-赤藓糖-4-磷酸D-erythrose 4-phosphate	Com_12658_pos	481393.16	2098673.97	4.36
L-色氨酸L-tryptophan	Com_8850_pos	2216018.31	5757659.85	2.60
L-酪氨酸L-tyrosine	Com_203_pos	1769276119.00	455236147.10	0.26
L-苯丙氨酸L-phenylalanine	Com_21_pos	11760291258.00	2213525450.00	0.19
吲哚Indole	Com_250_pos	1378106746.00	272702018.80	0.20

图9 苯丙氨酸的生物合成通路

Fig.9 Phenylalanine biosynthetic pathways

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