Metabolome of nematicidal fungus<i> Esteya vermicola</i> in carbon and nitrogen culture

LI Xingpeng; ZHANG Yang; WANG Ruizhen; DONG Leiming

doi:10.11833/j.issn.2095-0756.20210828

Volume 39 Issue 6

Nov. 2022

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LI Xingpeng, ZHANG Yang, WANG Ruizhen, DONG Leiming. Metabolome of nematicidal fungus Esteya vermicola in carbon and nitrogen culture[J]. Journal of Zhejiang A&F University, 2022, 39(6): 1313-1320. doi: 10.11833/j.issn.2095-0756.20210828

Citation:

LI Xingpeng, ZHANG Yang, WANG Ruizhen, DONG Leiming. Metabolome of nematicidal fungus Esteya vermicola in carbon and nitrogen culture[J]. Journal of Zhejiang A&F University, 2022, 39(6): 1313-1320. doi: 10.11833/j.issn.2095-0756.20210828

Metabolome of nematicidal fungus Esteya vermicola in carbon and nitrogen culture

doi: 10.11833/j.issn.2095-0756.20210828

1.
Forestry College, Beihua University, Jilin 132013, Jilin, China
2.
Jilin Provincial Academy of Forestry Sciences, Changchun 130033, Jilin, China
3.
Research Center of Horticultural Engineering and Technology of Beijing, Beijing Botanical Garden, Beijing 100093, China

Received Date: 2021-12-29
Accepted Date: 2022-05-31
Rev Recd Date: 2022-05-24

Available Online: 2022-11-21

Publish Date: 2022-12-20

Abstract

Objective The objective is to compare the metabolic differences of the nematode-killing fungus Esteya vermicola (EV) cultured in carbon and nitrogen nutrient sources and to identify key metabolites or signal molecules. Method The carbon medium (mainly composed of PDB) for culturing fungi and the nitrogen medium (mainly composed of yeast powder) for culturing bacteria were selected. EV bacteria were cultured on two kinds of culture media at 25 ℃ for 7 days. The mycelia were harvested and the metabolites were extracted. Non-target high performance liquid chromatography-mass spectrometry (HPLC-MS) was used to analyze and identify metabolite components in both positive and negative ion modes. The metabolic pathways of metabolites with significant differences were analyzed. Result A total of 498 metabolites were identified, including 176 negative and 362 positive ion modes and 40 metabolites in both modes. There were 444 metabolites with significant differences, accounting for 89.2% of the total, among which 162 were negative and 310 were positive, and 28 were common to the two modes. Both principal component analysis and partial least square discriminant analysis could cluster the metabolites into different clusters and separate them significantly in carbon and nitrogen culture. In nitrogen culture, guanidine phosphate acetate and p-cresol sulfate were abundant and unique metabolites, and the yield of allantoin, photopigment, indole, and trehalose were significantly up-regulated. Pathway analysis enriched the significantly up-regulated and down-regulated metabolites into the metabolic pathways related to amino acid and carbohydrate metabolism, respectively. Conclusion EV bacteria showed significant metabolic differences in carbon and nitrogen culture. The metabolic pathway mainly involves carbohydrate and amino acid metabolism. The important metabolites will provide a theoretical basis for efficient culture and application of EV. [Ch, 3 fig. 2 tab. 31 ref.]
- biocontrol fungi,
- Esteya vermicola,
- metabonomics,
- LC-MS

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沈阳化工大学材料科学与工程学院沈阳 110142

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松材线虫Bursaphelenchus xylophilus病在亚洲和欧洲造成严重的生态和经济损失^[1-2]，伊氏杀线虫真菌Esteya vermicola (EV菌)是松材线虫的内寄生真菌，产生的新月形孢子能侵染并杀死松材线虫，在松材线虫的生物防治方面具有良好的应用前景^[3]。同时，EV菌亦可侵染拟松材线虫B. mucronatus、水稻干尖线虫Aphelenchoides besseyi等线虫。研究表明：EV真菌胞内存在共生细菌^[4]，共生细菌对真菌的生物学和生态学具有重要的作用，如Rhizopus microsporus胞内的共生细菌Burkholderia能产生植物毒素根霉素，然后由宿主真菌分泌到环境中，导致水稻枯萎病^[5]。菌丝内的共生微生物(细菌或病毒)是重要的能直接或间接改变真菌和宿主关系的互作生物^[6-8]，提高宿主真菌的生态适应性^[9-10]。存在共生细菌的真菌对碳氮源如何响应，其代谢产物发生何种变化，目前尚未见相关报道。

代谢组学是系统生物学研究中非常重要的一个环节，旨在研究生物体或组织，甚至单个细胞的全部小分子代谢物成分及其动态变化^[11]。通过对代谢物质的分析，可以从生物样本中检测并筛选出具有重要生物学意义和显著差异的代谢物质，并以此为基础研究生物体的代谢过程和变化机制^[12]。对EV菌在不同碳、氮培养条件下代谢物的变化进行分析，明确显著差异代谢物，特别是重要的信号分子，不仅为EV菌的应用提供重要理论基础，而且对深入研究内共生细菌在EV菌的功能亦具有重要意义。

1. 材料与方法

1.1. 菌株

伊氏杀线虫真菌Esteya vermicola CBS115803购于荷兰菌物保存中心。

1.2. 培养基

碳培养基为24 g 马铃薯葡萄糖肉汤培养基(PDB，Becton， Dickinson and Company，美国)和10 g琼脂溶于1 L双蒸水。氮培养基为5 g酵母粉(OXOID公司，英国)和10 g琼脂溶于1 L双蒸水。

1.3. 仪器和试剂

Nano高分辨液质联用分析仪QE (Thermo Q-Exactive，德国)；赛多利斯BSA124S电子天平；真空浓缩仪(Labogene MaixVac Alpha, 丹麦)；Sigma 3-30KS高速离心机，KQ5 200DE型数控超声波清洗器(昆山市超声仪器有限公司，中国)；色谱级甲醇(Fisher，美国)。

1.4. 处理

配制碳、氮固体培养基，培养基凝固后放入已灭菌的尼龙膜(孔径3 μm，赛多利斯)，接种EV菌后于25 ℃培养7 d。将长满菌丝和孢子的尼龙膜用无菌镊子取出，用超纯水冲洗尼龙膜，再用无菌的吸水纸吸掉尼龙膜接触培养基面的水分，而后将菌丝和孢子刮入2 mL圆底灭菌干燥离心管，装样品前后分别称量离心管的质量，迅速将样品管放入液氮中淬灭后于−80 ℃保存。每处理设置5次生物学重复，编号依次为C₁~C₅和N₁~N₅。加入冷冻洁净无菌的直径为3 mm的钢珠2个，液氮冷冻条件下使用莱驰RETSCH MM 400研磨2 min。将研磨好的样品管置于干冰上，加入2 mL预冷的体积分数为80%甲醇于−80 ℃冰箱静置1 h，4 ℃、14 000 g离心20 min后将上清液转移至另一相同体积离心管，真空浓缩干燥样品后于−80 ℃保存。用300 μL体积分数为90%甲醇超声复溶并经0.45 μm的滤膜过滤，完成亲水代谢产物提取。

1.5. HPLC-MS分析

采用非靶标的高效液相色谱-质谱联用技术(HPLC-MS)对样品进行测定和代谢物识别。色谱柱：Waters ACQUITY UPLC®(2.1 mm×100.0 mm，1.7 μm)。流动相：0.1%甲酸-水溶液(A)，0.1%甲酸-乙腈(B)。洗脱条件：0~0.5 min，95%B；0.5~7.0 min，95%~65% B；7.0~8.0 min，65%~40% B；8.0~9.0 min，40%B；9.0~9.1 min，40%~95%B；9.1~12.0 min，95%B。质谱参数条件：鞘气，310 275 Pa；辅助气，103 425 Pa；喷雾电压，4 000 V (正)/3 500 V (负)；离子传输管温度：350 ℃。在采集软件(Xcalibur 4.0.27，Thermo)的控制下，采用一级质谱全扫描(全MS)结合自动触发二级质谱扫描(MS/MS)模式，使用阴、阳离子模式2种电离方式采集质谱数据。运行时间：0~18 min。分辨率：全MS，170000；MS/MS，17500。

1.6. 代谢物注释分析

对原始数据进行基线过滤、峰识别、积分、保留时间校正、峰对齐和归一化，最终得到1个保留时间、质荷比和代谢物信号(峰面积)的数据矩阵。将处理后的代谢物信号与一级和二级数据库进行匹配，将其中二级得分＜30的化合物可信予以剔除。分析时10份样品共插入3个质量对照(QC)样本以考察整个分析过程中仪器的稳定性，QC样本每种化合物的峰面积的变异系数若＞30%，则予以剔除。未检出值设定为0，缺失值由其余重复样品的均值填补。

1.7. 差异代谢物筛选

由Metaboanalyst 4.0在线软件(https://www.metaboanalyst.ca/MetaboAnalyst/home.xhtml)完成。利用对数转换和pareto缩放对各代谢物相对含量进行标准化处理。使用主成分分析法(PCA)和偏最小二乘法判别法(PLS-DA)评估不同处理的分组情况。结合以下2个标准对2种培养基的阴阳离子模式的差异化合物进行筛选：经FDR (false discovery rate)校正的t检验的P＜0.05；正交偏最小二乘判别分析(OPLS-DA)中变量投影重要性(variable influence on projection，VIP)得分＞1。

1.8. 代谢通路分析

代谢通路分析由Metaboanalyst 4.0 (https://www.metaboanalyst.ca/MetaboAnalyst/upload/PathUploadView.xhtml)中的代谢通路分析模块(pathway analysis module)完成。该分析将选定的差异代谢物与KEGG (Kyoto encyclopedia of genes and genomes)数据库(2019年10月)和人类代谢组数据库(HMDB)进行匹配，然后选择酵母Saccharomyces cerevisiae的代谢通路库作为参照进行富集分析和拓扑分析。富集分析中采用参数超几何法(hypergeometric test)检验每个代谢通路的显著性(P＜0.05)；拓扑分析中差异显著性检验的方法为相对介数中心性(relative-betweeness centrality)。

3. 讨论

本研究在代谢组水平探究含内共生细菌的生防真菌EV菌对不同碳氮培养基的化学响应，鉴定到一些差异显著的化合物，尤其是在氮源培养基中特有的代谢产物，并定位到重要代谢途径上。磷酸胍基乙酸酯和对甲酚硫酸盐是在氮培养下EV菌大量产生的特有代谢物，尿囊素、光色素、吲哚和海藻糖等是氮培养条件下显著上调的代谢物。对甲酚硫酸盐是细菌代谢酪氨酸的产物^[13]。已有研究证实：拟杆菌科Bacteroidaceae、双歧杆菌科Bifidobacteriaceae、梭菌科Clostridiaceae、肠杆菌科Enterobacteriaceae、肠球菌科Enterococcaceae、优杆菌科Eubacteriaceae、梭杆菌科Fusobacteriaceae、毛螺菌科Lachnospiraceae、乳杆菌科Lactobacillaceae、紫单胞菌科Porphyromonadaceae、葡萄球菌科Staphylococcaceae、疣微菌科Ruminococcaceae和韦荣氏菌科Veillonellaceae等细菌是对甲酚硫酸盐的产生菌^[14]。已有研究表明：细菌也可以降解对甲酚^[15]，真菌Trichosporon cutaneum和Aspergillus fumigatus也可以利用对甲酚作为碳源^[16-17]。因此推测：对甲酚硫酸盐可能是在高氮源培养下，由于碳源严重缺乏，EV菌胞内共生细菌代谢酪氨酸产生对甲酚或对甲酚硫酸盐，从而将其做为碳源进一步利用。

多种革兰氏阳性细菌和革兰氏阴性细菌(迄今为止共有85种)都会产生大量的吲哚。作为细胞间信号分子，吲哚控制细菌生理的多个方面，例如孢子形成、质粒稳定性、耐药性、生物膜形成和吲哚产生细菌的毒力^[18]。在细菌中，吲哚由氨基酸色氨酸的降解产物产生。吲哚是细菌Ⅲ型分泌系统表达的信号分子^[19]。EV真菌细菌共生体可产生吲哚，根据上述目前的研究只在细菌发现吲哚的产生，因此我们推测胞内细菌可能是吲哚的产生者，细菌可以利用吲哚这一信号分子协调两者行为，以在真菌胞内生存。

前期研究表明：EV菌基因组中含有比其他杀线虫真菌，如Arthrobotrys oligospora、Dactylellina haptotyla、Drechmeria coniospora更多的尿囊素转运蛋白^[20]。此外，EV菌胞内的共生细菌属于假单孢属Pseudomonas^[6]。尿囊素是腺嘌呤和鸟嘌呤代谢的中间产物，尿囊素可以被某些真菌、细菌和植物用作碳和氮的来源，尿囊素或尿囊素通路的衍生物可能有助于提高真菌向宿主植物提供氮的能力^[21]。如在一些外生菌根真菌中，已鉴定出尿囊素/尿囊酸转运蛋白^[21-22]。研究发现：假单孢属的细菌和酵母Saccharomyces cerevisiae也可以降解尿囊素^[23-24]。在氮源充足的氮培养条件下，尿囊素代谢产物约是碳培养条件下的32倍，因此，尿囊素很可能是EV菌供给胞内共生细菌氮源的一种形式。

海藻糖在自然界中分布广泛，包括细菌、真菌、植物、无脊椎动物和哺乳动物。由于其特殊的物理特性，海藻糖能够保护细胞的完整性免受各种环境损害和营养限制。细菌可以使用海藻糖作为碳和能量的唯一来源，一些分枝杆菌中海藻糖可作为细胞壁的结构成分，而酵母细胞在很大程度上不能以海藻糖为碳源生长^[25]。在根瘤菌-豆科Leguminosae植物共生期间，海藻糖在根瘤发育过程中被储存在根瘤中，并成为细菌的主要碳水化合物，而与所供应的碳源和氮源类型无关^[26]。内源性海藻糖在碳缺乏或在给定培养基中碳源耗尽后被动员。海藻糖很可能是EV共生细菌的一种碳源，在碳源缺乏时作为储备能源(氮培养下产生的海藻糖是碳培养下的2.5倍)。

光色素是核黄素的光敏分解产物。关于光色素的酶促转化路径已在假单胞菌等细菌中进行研究^[27]。已有研究认为：光色素是细菌群感效应的信号分子^[28]，是能影响植物生长的细菌信号分子^[29]，同时也是共生的信号分子^[30-31]。不同的营养条件(如氮和磷)可改变细菌产生光色素的浓度^[30]。本研究使用的氮源是有机氮源。在该氮培养下产生的光色素是碳培养下的8倍，氮培养条件下光色素的产量远高于碳培养条件，不同于前人报道的高浓度硝酸盐降低光色素的产量^[30]。

差异最显著的代谢物多数未能富集到显著的代谢通路，原因在于这些化合物的代谢通路尚未研究透彻，或者它们是EV菌的特异化合物，尚未包括在参照数据库中。无论以真菌还是细菌数据库为参照，富集到的显著代谢通路基本一致，均与氨基酸和糖类代谢相关，而这些通路是真菌和细菌共有的，无法区分内共生细菌对其真菌宿主代谢的影响。笔者曾试图利用多种抗生素去除内共生细菌以解决该问题，并未获得成功，需要更深入的研究。

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化合物名称	质荷比	保留时间/min	二级数据库得分	变化倍数	P	KEGG编号
磷酸胍基乙酸酯	198.03	9.86	62	12.46	1.13×10⁻¹³	C03166
对甲酚硫酸盐	187.01	6.17	53	12.41	8.88×10⁻¹⁵
邻氨基苯甲酸酯	136.04	2.00	50	9.93	1.67×10⁻⁸	C00108
尿酸	190.05	1.29	40	8.26	6.26×10⁻⁷	C01717
尼古丁	163.12	4.68	44	5.51	1.14×10⁻⁶	C16150
4-羟基-2-喹啉羧酸	188.03	5.76	30	5.48	9.62×10⁻⁸	C01717
烟酸	124.04	3.50	41	5.17	1.71×10⁻⁷	C00253
尿囊素	159.05	5.46	50	5.09	2.53×10⁻⁴	C01551
吲哚丙烯酸	188.07	7.98	98	4.20	4.68×10⁻⁸
2-吡咯烷酮	86.06	3.79	41	4.10	2.57×10⁻⁵	C11118
咪唑乙酸	127.05	9.62	69	3.54	1.56×10⁻⁷	C02835
组胺	112.09	5.74	45	3.34	2.79×10⁻⁸	C00388
谷胱甘肽	306.08	1.02	58	3.26	5.97×10⁻⁴	C00051
光色素	243.09	1.58	70	3.00	2.79×10⁻⁴	C01727
肌肽	227.11	12.66	55	2.40	3.30×10⁻⁵	C00386
甜菜碱醛	102.09	6.73	68	2.25	9.68×10⁻³	C00576
吲哚	118.07	8.32	57	2.12	4.40×10⁻³	C00463
苹果酸	133.01	0.90	43	1.90	2.86×10⁻⁵	C00711
甜菜碱	118.09	8.30	51	1.88	2.79×10⁻⁸	C00719
胍基乙酸d	118.06	8.26	38	1.87	1.19×10⁻³	C00581
葫芦巴碱	138.06	9.05	38	1.59	1.71×10⁻⁷	C01004
海藻糖	341.11	1.04	78	1.34	6.16×10⁻⁵	C01083
左旋肉碱	162.11	9.31	72	1.34	2.97×10⁻⁶	C00318
邻乙酰左旋肉碱	204.12	8.54	73	1.32	1.69×10⁻⁶	C02571
茶碱	181.07	2.24	55	−1.64	6.07×10⁻⁷	C07130
二乙醇胺	106.09	8.16	45	−1.73	1.42×10⁻⁴	C06772
去甲肾上腺素	170.08	5.83	57	−2.40	1.52×10⁻⁵	C00547
阿魏酸盐	193.05	5.36	32	−3.58	2.87×10⁻⁵	C01494
核糖醇	151.06	1.01	46	−4.08	3.13×10⁻⁸	C00474
甲基咪唑乙酸	141.07	9.52	41	−4.51	2.90×10⁻⁸	C05828
赤藓糖醇	121.05	1.04	75	−5.20	2.80×10⁻⁵	C00503

	代谢通路编号	代谢通路名称	匹配情况	P	影响大小
上调	sce00970	氨酰基tRNA的生物合成	18/46	4.38×10⁻⁴	0.11
	sce00330	精氨酸和脯氨酸代谢	10/25	7.53×10⁻³	0.33
	sce00220	精氨酸生物合成	8/18	8.05×10⁻³	0.60
	sce00430	牛磺酸和低牛磺酸代谢	4/7	2.28×10⁻²	1.00
	sce00250	丙氨酸、天冬氨酸和谷氨酸代谢	8/22	3.06×10⁻²	0.81

下调	sce00520	氨基糖和核苷酸糖代谢	8/24	3.41×10⁻⁴	0.48
	sce00052	半乳糖代谢	5/17	8.98×10⁻³	0.82
	sce00040	戊糖和葡萄糖醛酸的相互转化	4/12	1.22×10⁻²	0.27
	sce00500	淀粉和蔗糖代谢	4/15	2.79×10⁻²	0.35
说明：匹配情况为匹配化合物个数/通路化合物总数