药学学报  2021, Vol. 56 Issue (4): 1178-1187     DOI: 10.16438/j.0513-4870.2020-1771   PDF    
艾比湖盐碱地肉苁蓉与锁阳土壤微生物群落分析
郑燕1,3, 孙晓1,2, 缪雨静1,2, 江媛1,4, 阿里穆斯5, 黄林芳1,2     
1. 中国医学科学院、北京协和医学院药用植物研究所, 国家中医药管理局中药资源保护重点研究室, 北京 100193;
2. 中药资源教育部工程研究中心, 北京 100193;
3. 江西中医药大学, 江西 南昌 330000;
4. 大理大学, 云南 大理 671000;
5. 民族医药教育部重点实验室 (中央民族大学), 中央民族大学药学院, 北京 100081
摘要: 为探讨极端生境-盐碱地下两种典型寄生药用植物肉苁蓉与锁阳的土壤微生物群落特点,本文基于微生物组-生态因子策略,对新疆艾比湖的肉苁蓉与锁阳土壤进行16S扩增子测序,分析土壤微生物群落的组成,并结合核心微生物组丰度及生态气候因子进行冗余分析和相关性分析。结果表明肉苁蓉土壤微生物群落多样性显著高于锁阳,肉苁蓉与锁阳核心微生物组为海单胞菌属Marinomona、盐单胞菌科Halomonadaceae、根瘤菌目Rhizobiales、嗜盐单胞菌属Halomonas及Acidimicrobiales。可区别二者土壤微生物群落的6个特异性生物标记物为微球菌科Micrococcacea、EchinicolaGlutamicibacterGalbibacter,假交替单胞菌属PseudoalteromonasMarinobacterium_rhizophilum。冗余分析和相关性分析结果表明最干季度平均温度与最冷季度平均温度、粘土含量及土壤质地分类是影响肉苁蓉与锁阳土壤微生物群落组成的主要生态因子。本文为后期寻找肉苁蓉与锁阳的微生物分子标记,促进品质提高提供理论依据。
关键词: 肉苁蓉    锁阳    土壤微生物群落    生态因子    
Analysis of the soil microbial community of Cistanche deserticola and Cynomorium songaricum in the saline-alkali soil of Ebinur Lake
ZHENG Yan1,3, SUN Xiao1,2, MIAO Yu-jing1,2, JIANG Yuan1,4, BORJIGIDAI Almaz5, HUANG Lin-fang1,2     
1. Key Lab of Chinese Medicine Resources Conservation, State Administration of Traditional Chinese Medicine of China, Institute of Medicinal Plant Development, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100193, China;
2. Engineering Research Center of Chinese Medicine Resource, Ministry of Education, Beijing 100193, China;
3. Jiangxi University of Traditional Chinese Medicine, Nanchang 330000, China;
4. Dali University, Dali 671000, China;
5. Key Laboratory of Ethnomedicine(Minzu University of China), Ministry of Education, School of Pharmacy, Minzu University of China, Beijing 100081, China
Abstract: To explore the characteristics of soil microbial communities of Cistanche deserticola and Cynomorium songaricum, two typical parasitic medicinal plants that live in an extreme saline alkali environment, 16S PCR was used to sequence the soil microbial communities of C. deserticola and C. songaricum in Ebinur Lake, Xinjiang. Redundancy analysis and correlation analysis were carried out based on the abundance of core microbiome and ecoclimatic factors. The results show that the diversity of the soil microbial community of C. deserticola was significantly higher than that of C. songaricum. The core microbial groups of C. deserticola and C. songaricum were Marinomona, Halomonadaceae, Rhizobiales, Halomonas, and Acidimicrobiales. Six specific biomarkers were identified as Micrococcacea, Echinicola, Glutamicibacter, Galbibacter, Pseudoalteromonas, and Marinobacterium_rhizophilum. The results of redundancy analysis and correlation analysis show that the average temperature in the driest season and the average temperature in the coldest season, and the clay content and soil texture classification were the main ecological factors affecting the composition of these soil microbial communities. This study provides a theoretical basis for finding molecular markers of C. deserticola and C. songaricum and promoting the quality of C. deserticola and C. songaricum.
Key words: Cistanche deserticola    Cynomorium songaricum    soil microbial community    ecological factor    

艾比湖地区位于中纬度地带的西北干旱区, 是国内最具代表性的温带干旱区湿地荒漠生态系统[1], 盐碱化土壤广泛分布[2]。其典型的植被群落有梭梭群落、芦苇群落、盐节木群落和盐角草群落等[3]。鉴于其生境的特殊性, 近几年国内外学者对艾比湖周边植物微生物群落进行了大量研究。Jin等[4]应用Illumina HiSeq PE250测序技术, 分析6个土壤样本固氮微生物的多样性, 结合相关的理化因子并利用RDA分析法探究土壤理化性质和固氮微生物菌落结构及相关性; Yang等[5]从艾比盐湖中分离出的一种水解淀粉且极嗜盐的古细菌[BD-3 (T) 菌株], 并进行了表型和基因型分析, 确定其分类地位。Xin等[6]从艾比湖中分离出了一种新型的极嗜盐古细菌XF10T。

肉苁蓉与锁阳均为艾比湖盐碱地特殊生境下的全寄生药用植物, 肉苁蓉Cistanche deserticola Y. C. Ma为列当科肉苁蓉属寄生植物[7], 又名大芸, 为药食两用植物, 主要分布在北非、阿拉伯和亚洲国家。在中国、韩国和日本, 肉苁蓉肉质茎通常被用作补品, 以改善记忆力、增强性功能、保护肝脏、补肾等[8]。锁阳(Cynomorium songaricum) 为锁阳科(Cynomoriaceae) 锁阳属(Cynomorium) 多年生肉质寄生草本植物, 多寄生于蒺藜科(Zygophyllaceae) 白刺属(Nitraria) 植物的根部, 属专性根寄生植物[9, 10], 具有调节肾功能、提高机体免疫力、抗氧化等广泛的药理作用[11]。锁阳属荒漠植物, 药用资源主要分布在甘肃、内蒙古、新疆、宁夏等地区的沙漠和半沙漠地带[12]。肉苁蓉的寄主植物为梭梭(Haloxylon ammodendron) 及白梭梭(Haloxylon persicum), 锁阳的寄主植物为白刺属(Nitraria L.)、红砂属(Reaumuria L.)、猪毛菜属(Salsola L.) 等[13]

土壤微生物组是陆地生态系统植物多样性和生产力的重要驱动因素, 直接参与了植物获得养分和土壤养分循环两个过程, 充分研究药用植物土壤微生物, 可以发挥土壤微生物组在改善植物营养、提高养分利用率和降低化肥施用量方面的作用[14]。Yue等[15]表征了菊芋沿土壤盐度梯度生长的微生物群落结构和盐渍土的各种特性, 并使用RDA分析和基因组组装在沿海盐渍土壤上进行了扩增以及宏基因组测序, 鉴定了对盐胁迫具有高响应能力并可能在盐渍土中起关键作用的微生物, 强调了古细菌在微生物群落响应中的重要作用盐胁迫; Ai等[16]采用高通量测序技术对野生竹叶兰根围土壤、根表、根内3个生态位真菌的种类及生物学功能进行鉴定与预测, 为揭示竹叶兰与根系真菌的营养关系以及共生真菌的开发提供了依据; Dong等[17]基于MetaCoMET与共存网络两种方法对采自湖南、四川和贵州的药用杜仲树皮真菌群落进行了核心真菌组分析, 表明在OTU (operational taxonomic units) 水平上, 核心真菌组共有16个分类单元, 优势菌是丛赤壳科一未定真菌, 其次为Fusarium pseudensiforme、一种黄丝菌Cephalothecaceae sp.和一种镰刀菌Fusarium sp.等。研究相同生境下肉苁蓉与锁阳土壤微生物能进一步为“中药品质生态学”理论提供支撑。

肉苁蓉与锁阳具有“补肾阳, 益精血”[18]的作用, 且均为典型的特殊生境下的全寄生植物, 为研究二者土壤微生物差异, 本研究通过对肉苁蓉和锁阳的土壤进行16S扩增子测序, 分析比较两物种土壤微生物群落组成和功能差异, 并结合产地附近的生态气候及土壤数据, 通过对微生物组-生态因子的相关性分析探讨影响肉苁蓉与锁阳土壤微生物群落的潜在生态机制, 为道地药材品质生态学理论研究提供科学依据。

材料与方法

材料   本研究实验材料肉苁蓉(ABR1、ABR2、ABR3) 与锁阳(ABS1、ABS2、ABS3、ABS4) 样品(表 1) 于2017年5月采集自新疆艾比湖。将表面土层挖开, 露出肉苁蓉与锁阳, 将样品10 cm处土壤一起取出并装入无菌袋, 放置于干冰中冻存后, 运到实验室。后将土壤样品过2 mm筛, 除去植物组织、根和石块等, 置于-20 ℃的冰箱中。

Table 1 Species sample information and operational taxonomic units (OTU) results

DNA提取及16S扩增子测序   使用DNA Kit (Omega Bio-tek, Norcross, GA, U.S.) 对收集到的8组样品提取DNA, 获得的DNA用1%琼脂糖凝胶电泳检测和分光光度法(260 nm/280 nm光密度比) 质量检测。肉苁蓉与锁阳土壤微生物多样性检测: 选取细菌16S rDNAV3-V4区, DNA样本送至北京奥维森基因科技有限公司, 利用Illumina Miseq PE300高通量测序平台测序。细菌16S rDNA V3-V4扩增引物为338F (5′-ACTCCTACGGGAGGCAGCAG-3′) 和806R (5′-GGA CTACNNGGGTATCTAAT-3′)。PCR反应体系(总体系为25 μL): 12.5 μL KAPA 2G Robust Hot Start Ready Mix、1 μL Forward Primer (5 μmol·L-1)、1 μL Reverse Primer (5 μmol·L-1)、5 μL DNA (加入的DNA总量为30 ng), 最后加5.5 μL dd H2O补足至25 μL。反应参数: 95 ℃预变性5 min; 95 ℃变性45 s, 55 ℃退火50 s, 72 ℃延伸45 s, 28个循环; 72 ℃延伸10 min。测序原始序列上传至NCBI的SRA数据库。

数据统计分析   通过Illumina MiSeq平台进行Paired-end测序, 下机数据经QIIME (v1.8.0) 软件过滤、拼接、去除嵌合体, 去除打分低于20、碱基模糊、引物错配或测序长度小于150 bp的序列。根据barcodes归类各处理组序列信息, 聚类为用于物种分类的OTU, OTU相似性设置为97%。通过RDP Classifier (http://rdp.cme.msu.edu/classifier/classifier.jsp) 算法基于细菌数据库(Silva 128) 对OTU代表序列进行比对分析, 并在界、门、纲、目、科、属水平注释群落的物种信息。使用R中ggplot2包绘制物种在门水平和属水平上的丰度直方图及饼图。再利用Mothur软件(version 1.31.2) 进行α多样分析(包括Shannon、Simpson、observed species和Chao1等4个指数)。基于Unweighted Unifrace距离, 使用R (v3.1.1) 软件包的pheatmap进行聚类分析。经过UniFrac算法利用系统进化的信息比较样品间物种群落差异, 并进行beta多样性(beta diversity) 分析。通过在线分析网站Microbiome Analyst (http://www.microbiomeanalyst.ca/) 获得核心微生物组(Core microbiome), 结合LDA Effect Size (LEfSe)[19]及随机森林(Random forest) 分析预测生物标记物。使用TBtools[20]绘制核心微生物组及生物标记物的丰度热图。

结果与分析 1 肉苁蓉与锁阳土壤微生物群落组成特征

对艾比湖周边的7个肉苁蓉与锁阳土壤细菌样品16S DNA的V3和V4区域进行高通量测序, 经数据前处理质控后, 分析得到18 122~34 142条待分析数据(clean reads)。经聚类分析, 7个样品含3 582个可操作分类单元(OTU) (表 1), 其中肉苁蓉样品OTU介于1 082~1 145, 锁阳样品OTU介于523~1 063。基于非加权unifrac距离的非度量多维尺度分析(non-metric multidimensional scaling, NMDS) 结果(图 1a) 显示, 肉苁蓉与锁阳土壤微生物群落明显区分。非加权unifrac距离聚类结果(图 1b) 显示两个物种土壤样品微生物群落被聚为两支, 表明7个土壤样本组间差异大于组内差异。

Figure 1 Clustering information of soil microorganisms of C. deserticola and C. songaricum. (a) PCoA plot based on the unweighted UniFrac distance matrix of the 16S rRNA gene amplicons; (b) Based on unweighted unifrac distance diversity clustering tree

两个物种的土壤中, 细菌类群主要包括16门、46纲、73目、100科及130属。肉苁蓉土壤中优势菌门(图 2ad) 为变形菌门Proteobacteria (48.91%)、放线菌门Actinobacteria (18.79%) 和拟杆菌门Bacteroidetes (16.03%) 等。属水平上的优势菌属(图 2b2d) 为Echinicola (7.4%)、嗜盐单胞菌属Halomonas (7.11%) 和海杆菌属Marinobacter (4.73%) 等。锁阳土壤中优势菌门(图 2a2e) 为变形菌门Proteobacteria (70.54%)、拟杆菌门Bacteroidetes (10.86%)和放线菌门Actinobacteria (7.89%)。属水平上的优势菌属(图 2b2e) 为海单胞菌属Marinomonas (8.62%)、嗜盐单胞菌属Halomonas (7.46%) 和假交替单胞菌属Pseudoalteromonas (6.37%)。图 2c显示了门水平上细菌类群的系统进化关系, 圆形大小显示了细菌群落的丰度。图 2d2e分别展示了肉苁蓉和锁阳丰度前六的菌门及丰度前十五的属类别。结果表明, 肉苁蓉与锁阳土壤微生物的优势菌群类别在门和属水平上总体相似, 但其丰度存在差异。

Figure 2 Classification of microbial community composition of C. deserticola and C. songaricum. a: Histograms of phyla abundances; b: Histograms of genus abundances; c: Phylogenetic tree at the phylum level; d: Pie chart of the top 6 microbial phylum-level species and their top 15 genus-level of C. deserticola; e: Pie chart of the top 6 microbial phylum-level species and their top 15 genus-level of C. songaricum; f: Within-sample diversity (α-diversity). ACE, which is used as an indicator of species richness in ecology. The higher the value, the richer the community species. Chao1 index, which indicates the bacterial community richness (expressed as the projected total number of OTU in each sample). Fisher, in which along with the number (richness), the abundance of organisms (evenness) is also measured to describe the actual diversity of a community. g: Heatmap of core microbial abundance of C. deserticola and C. songaricum. ABR: C. deserticola; ABS: C. songaricum. OTU_527: Marinomonas, OTU_512: Halomonadaceae, OTU_6219: Rhizobiales, OTU_1569: Halomonas, OTU_6252: Actinobacteria, OTU_685: Halomonas

Alpha多样性(样本内多样性) 指一个特定区域或者生态系统内的多样性, 常用的度量指标有Chao1丰富度估计量(Chao1 richness estimator)、香农-威纳多样性指数(Shannon-Wiener diversity index)、辛普森多样性指数(Simpson diversity index) 等, 且数值越大, 群落多样性越高[21]图 2f显示, ACE、Chao1、Fisher、observed species、Shannon和Simpson六个多样性数值结果一致, 肉苁蓉均高于锁阳, 表明肉苁蓉土壤微生物多样性高于锁阳。

根据OTU的样本最小百分比及相对丰度获得的肉苁蓉与锁阳土壤核心微生物组为海单胞菌属Marinomonas (OTU_527)、盐单胞菌科Halomonadaceae (OTU_512)、根瘤菌目Rhizobiales (OTU_6219)、嗜盐单胞菌属Halomonas (OTU_1569)、Acidimicrobiales (OTU_6252) 及嗜盐单胞菌属Halomonas (OTU_685) 等。核心微生物组丰度热图(图 2g) 显示, 肉苁蓉与锁阳土壤中盐单胞菌科Halomonadaceae (OTU_512)、根瘤菌目Rhizobiales (OTU_6219) 丰度较高。

2 肉苁蓉与锁阳土壤微生物群落差异分析

LEfSe分析可以实现分组比较的内部进行亚组比较分析, 从而找到组间在丰度上有显著差异的生物标记物[1]图 3a列举了LDA score大于2的前15个生物标记物。采用随机森林方法(n = 1 000) 鉴定了6个肉苁蓉及锁阳土壤微生物生物标记物, 见3c。图 3b表明随机森林方法设置参数为1 000个树时, 整体的错误率最低(error = 0)。肉苁蓉土壤微生物微球菌科Micrococcacea (OTU_4258)、Echinicola (OTU_3086)、Glutamicibacter (OTU_4625) 与锁阳土壤微生物Galbibacter (OTU_2920)、假交替单胞菌属Pseudoalteromonas (OTU_734)、Marinobacterium_rhizophilum (OTU_861) 热图显示丰度较高, 与LDA得分值结果相呼应。肉苁蓉和锁阳土壤样品共有OTU为1 005, 肉苁蓉土壤样品特有OTU为1 263, 锁阳土壤样品特有OTU为1 186, 表明肉苁蓉土壤微生物丰度高于锁阳, 与图 2f结果一致(图 3c)。

Figure 3 Differential microbial profiles of C. deserticola and C. songaricum. a: Graphical summary at OTU level in group sample type of the top 15 biomarkers by LEfSe; b: Cumulative error rates obtained through RF classification. The overall error rate is represented by the red line, whilst the error rates for each class are represented by the green and blue lines. c: Heatmap of biomarkers microbiome abundance of C. deserticola and C. songaricum; d: Common/unique OTU of C. deserticola and C. songaricum; A: C. deserticola; B: C. songaricum. OTU_734: Pseudoalteromonas; OTU_861: Marinobacterium_rhizophilum; OTU_233: Gammaproteobacteria; OTU_190: Acinetobacter_calcoaceticus; OTU_2888: Sphingobacteriaceae; OTU_113: Gemmatimonadetes; OTU_2936: Gillisia; OTU_393: Rhodothermaceae; OTU_166: Bacillus; OTU_4258: Micrococcacea; OTU_3086: Echinicola; OTU_4625: Glutamicibacter; OTU_2920: Galbibacter
3 两个物种气候及土壤因子分析

本研究气候变量数据来自WorldClim数据库(https://www.worldclim.org/) 1970~2000年的监测数据。包含18个生态因子, 分别为年均温(bio 1)、昼夜温差月均值(bio 2)、等温性(bio 3)、温度季节性变化标准差(标准偏差×100) (bio 4)、最暖月最高温(bio 5)、最冷月最低温(bio 6)、年均温变化范围(bio 7)、最湿季度平均温度(bio 8)、最干季度平均温度(bio 9)、最暖季度平均温度(bio 10)、最冷季度平均温度(bio 11)、年平均降水量(bio 12)、最干月降水量(bio 13)、降水量变异系数(bio 14)、最湿季度降水量(bio 15)、最干季度降水量(bio 16)、最暖季度降水量(bio 17)、最冷季度降水量(bio 18), 见表 2

Table 2 The climatic factors of C. deserticola and C. songaricum. bio 1 = Annual mean temperature (℃×10); bio 2 = Mean diurnal range [mean of monthly (max temp-min temp)]; bio 3 = Isothermality (bio 2/bio 7) (×100); bio 4 = Temperature seasonality (standard deviation ×100); bio 5 = Max temperature of warmest month (℃×10); bio 6 = Min temperature of coldest month (℃×10); bio 7 = Temperature annual range (bio 5 - bio 6); bio 8 = Mean temperature of wettest quarter (℃×10); bio 9 = Mean temperature of driest quarter (℃×10); bio 10 = Mean temperature of warmest quarter (℃×10); bio 11 = Mean temperature of coldest quarter (℃×10); bio 12 = Annual precipitation (mm); bio 13 = Precipitation of driest month (mm); bio 14 = Precipitation seasonality (coefficient of variation); bio 15= Precipitation of wettest quarter (mm); bio 16 = Precipitation of driest quarter (mm); bio 17 = Precipitation of warmest quarter (mm); bio 18 = Precipitation of coldest quarter (mm)

土壤数据来自数据库HWSD (https://geodata.pku.edu.cn/index.php?c=content&a=show&id=730)。根据采样点经纬坐标, 通过Arcgis的“多值提取至点”工具提取样本土壤信息, 后挑选出与植物生长相关的13个土壤因子, 包括: 基本饱和度(T_BS)、黏性层土壤的阳离子交换能力(T_CEC_CLAY)、粘土含量(T_CLAY)、土壤的阳离子交换能力(T_CEC_SOIL)、可交换钠盐(T_ESP)、碎石体积百分比(T_GRAVEL)、有机碳含量(T_OC)、酸碱度(T_PH)、土壤容量(T_REF_BULK)、沙含量(T_SAND)、淤泥含量(T_SILT)、交换性盐基(T_TEB)、USDA土壤质地分类(T_USDA_TEX), 见表 3

Table 3 The soil factors of C. deserticola and C. songaricum. T_BS = Basic saturation; T_CEC_CLAY = Cation exchange capacity of clay soil; T_CLAY = Clay content; T_CEC_SOIL = Soil cation exchange capacity; T_ESP = Exchangeable sodium salt; T_GRAVEL = Volume percentage of gravel; T_OC = Organic carbon content; T_PH = PH; T_REF_BULK = Soil capacity; T_SAND = Sand content; T_SILT = Silt content; T_TEB = Exchangeable base; T_USDA_TEX = USDA soil texture classification
4 相关性分析

基于微生物群落-生态因子相关性分析的研究新体系, 对肉苁蓉与锁阳10个土壤核心微生物组的丰度与18个气候因子数据及13个土壤因子进行相关性分析, 以分析相同产地的不同物种的土壤微生物群落组成特征差异的生态机制。首先利用CANOCO 5软件[22]分析DCA (species-sample) 结果, 筛选RDA和CCA的模型[15]。DCA分析结果纵径长度(lengths of gradient) 的第一轴值为1.16 (小于4), 故本研究选用RDA模型进行分析。为挖掘影响肉苁蓉与锁阳土壤微生物群落结构的主导生态因素, 根据Effects值进行重分析, 方差解释变量为58.7%。结果(表 4图 4a) 表明土壤质地分类(T_USDA_TEX, P = 0.18, F = 2.1)、最干季度平均温度(bio 9, P = 0.516, F = 0.8)、等温性(bio 14, P = 0.5, F = 0.7)、粘土含量(T_CLAY, P = 0.914, F = 0.2) 与肉苁蓉及锁阳核心微生物组及生物标记物相关。

Table 4 Redundancy analysis of bacterial communities and ecological factors

Figure 4 Correlation analysis based on key microbiomes (six core microbiomes and six biomarkers), 18 ecological factors and 13 soil factors. a: RDA plot of overall key microbiomes, biomarkers, ecological factors, and soil factors by Canoco; b: Heatmap for correlation analysis of the key microbiomes, ecological factors, and soil factors of C. deserticola and C. songaricum; c: Core microbiomes abundance networks of C. deserticola reveal that OTU modules are related to ecological factors and soil factors; d: Key microbiomes abundance networks of C. songaricum reveal that OTU modules are related to ecological factors and soil factors

Pearson相关性分析结果(图 4b) 与RDA结果(图 4a) 相呼应, 最干季度平均温度(bio 9) 与最冷季度平均温度(bio 11) 对Alphaproteobacteria (OTU_6219) 及微球菌科Micrococcacea (OTU_4258) 呈显著负相关。粘土含量(T_CLAY) 及土壤质地分类(T_USDA_ TEX) 与假交替单胞菌属Pseudoalteromonas (OTU_734) 呈极显著负相关。粘土含量(T_CLAY)、交换性盐基(T_TEB) 及土壤质地分类(T_USDA_TEX) 对Marinobacterium_rhizophilum (OTU_861) 有显著影响。

为分析肉苁蓉与锁阳特有微生物与生态因子相关性, 利用肉苁蓉与锁阳10个核心微生物组与18个气候因子数据及13个土壤因子进行相关性分析。采用Pearson相关系数, 选择系数值绝对值大于0.5的值, 采用Cytoscape 3.7.1[23]构建核心微生物组-生态因子网络图。图 4c图 4d分别展示了肉苁蓉与锁阳土壤核心微生物与生态因子的关联网络。肉苁蓉土壤生物标记物土壤微生物微球菌科Micrococcacea (OTU_4258) 与最暖季度降水量(bio 17) 呈极显著正相关。土壤中盐单胞菌科Halomonadaceae (OTU_512) 与Marinobacterium_rhizophilum (OTU_861) 受环境影响较大。

锁阳土壤核心微生物组中(图 4d), Glutamicibacter (OTU_4625) 与最暖季度降水量(bio 17) 呈极显著负相关, 与最湿季度降水量(bio 15) 呈显著正相关。嗜盐单胞菌属Halomonas (OTU_685) 与年均温(bio 1)、昼夜温差月均值(bio 2)、等温性(bio 3)、最暖月最高温(bio 5)、最湿季度平均温度(bio 8) 及降水量变异系数(bio 14) 呈负显著相关。根瘤菌目Rhizobiales (OTU_6219) 与最干月降水量(bio 13) 及基本饱和度(T_BS) 呈极显著负相关, 与可交换钠盐(T_ESP) 呈显著正相关。两个网络关联图显示, 生态因子对于肉苁蓉土壤微生物群落组成的影响更大。

讨论

本研究对新疆艾比湖肉苁蓉和锁阳土壤进行微生物组-生态因子的综合相关性分析, 且比较两个物种共有核心微生物组和特异微生物组, 结合两个产地10个核心生物群落丰度及18个气候生态因子数据与13个土壤因子进行冗余和相关性分析, 挖掘影响肉苁蓉和锁阳土壤微生物群落组成和功能的生态因子。

取样地点位于新疆艾比湖湿地自然保护区, 是准噶尔盆地西部最低洼地和水盐的汇集中心。保护区东西长102.63 km, 南北宽72.3 km, 总面积2 670.85 km2, 地跨精河县、博乐市和阿拉山口口岸区, 92%在精河县内。本研究表明肉苁蓉与锁阳核心微生物组为海单胞菌属Marinomona、盐单胞菌科Halomonadaceae、根瘤菌目Rhizobiales、嗜盐单胞菌属Halomonas及Acidimicrobiales。Halomonas细菌菌株是嗜盐菌, 高浓度的NaCl为最佳生长条件, 研究表明, 在无盐条件, pH 7.0~10.0时也能生长, 它能积累甘氨酸甜菜碱、胞外酸和谷氨酸, 作为渗透保护剂[24], 说明盐单胞菌科Halomonadaceae及嗜盐单胞菌属Halomonas对肉苁蓉与锁阳具有渗透保护作用, 增加抗盐碱胁迫能力。

艾比湖地区属典型的大陆性干旱气候, 年降水量约105.17 mm, 年蒸发量约2 221.3 mm, 年平均气温7.7 ℃, 最高气温42.23 ℃, 最低气温-36.4 ℃, 年日照时数2 699.87 h[25], 盐碱胁迫与冷热胁迫严重。内蒙古与甘肃锁阳土壤样本的采样点均属于温带大陆性气候, 处于寒冷干旱的戈壁沙漠地带, 气温日较差、年较差均较大, 气候干燥, 太阳辐射能强, 并且土壤贫瘠, 极端气候频繁, 干旱胁迫及冷热胁迫严重。本课题组[1]前期研究表明, 在内蒙古及甘肃锁阳土壤中5个核心微生物组是节杆菌属Arthrobacter、链霉菌属Streptomyces、芽孢杆菌属Bacillus、副球菌属Paracocccus和鞘氨醇单胞菌属Sphingomonas, 为促进植物生长的根际细菌(PGPR), 具有在干旱环境下增强植物抵御干旱胁迫的能力, 但在该研究中, 锁阳土壤微生物中含0.06%节杆菌属Arthrobacter、0.05%链霉菌属Streptomyces、0.31%芽孢杆菌属Bacillus及0.03%鞘氨醇单胞菌属Sphingomonas。造成这种差异原因可能为内蒙古及甘肃地区干旱胁迫较艾比湖地区强。

不同生境下锁阳核心微生物差异较大, 基于本课题组前期提出的“中药品质生态学”理论[26], 微生物群落与中药的质量密切相关, 可进一步提出艾比湖与内蒙产锁阳是否质量也存在较大差异, 是否可以根据微生物群落预测植物最佳生态产区。后期本课题组也会进一步关注艾比湖产锁阳与内蒙产的品质质量, 对上述问题进行深入研究讨论。

本研究基于LEfSe法和随机森林方法得到肉苁蓉与锁阳土壤微生物群落的6个差异生物标记物, 其中在肉苁蓉样本中得分较高的为微球菌科Micrococcacea、EchinicolaGlutamicibacter, 锁阳样本中得分较高的为Galbibacter、假交替单胞菌属PseudoalteromonasMarinobacterium_rhizophilum。差异生物标记物不仅可鉴别不同产地锁阳的土壤微生物群落, 还是影响肉苁蓉与锁阳品质变异的潜在因子[1]

本研究结合6个核心微生物组及生物标记物, 获得肉苁蓉与锁阳土壤的关键微生物组。将关键微生物组的丰度与生态因子的冗余分析和关联分析发现, 同时影响肉苁蓉与锁阳土壤微生物群落组成的主要生态因子是最干季度平均温度与最冷季度平均温度、粘土含量、土壤质地分类。与本课题组前期研究[10]发现影响锁阳生长的主要生态因子是年相对湿度及1月和7月平均温度相符。生态环境因子对药用植物次生代谢物合成积累具有重要影响[27], 本研究表明, 气候因子(最干季度平均温度与最冷季度平均温度) 与土壤因子(粘土含量、土壤质地分类) 对肉苁蓉与锁阳微生物具显著影响, 三者进一步影响药材质量, 故明晰气候因子对微生物的影响能为建立药材优质生产基地提供科学依据。

通过对肉苁蓉和锁阳土壤微生物分析, 明晰了特殊生境下的两种全寄生药用植物的土壤微生物, 丰富了艾比湖地区土壤微生物资源。研究结果为后期寻找肉苁蓉与锁阳的微生物分子标记, 促进肉苁蓉与锁阳生长、分子育种及品质提高研究奠定基础。

作者贡献:  实验设计为黄林芳, 实验实施为郑燕和孙晓, 缪雨静、江媛与阿里穆斯进行实验评估, 郑燕执笔, 通讯作者审校。

利益冲突:  不涉及任何利益冲突。

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