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獼猴桃潰瘍病病原菌MLVA分型引物的篩選及驗證

2024-06-30 12:38:12姚令王海黃露安星宇陳文王莉爽薛原吳石平
果樹學報 2024年6期
關(guān)鍵詞:研究

姚令 王海 黃露 安星宇 陳文 王莉爽 薛原 吳石平

摘? ? 要:【目的】篩選出一組可精準快速地對丁香假單胞菌獼猴桃致病變種(Pseudomonas syringae pv. actinidiae,Psa)進行分型的引物組合。【方法】針對前期文獻已報道的34對引物,采用PCR技術(shù)驗證該34對引物對中國Psa菌株的擴增效率及準確性;利用模擬PCR獲取菌株串聯(lián)重復(TR)數(shù);以辛普森指數(shù)(Simpsons index,SI)作為篩選引物組合的標準,基于R軟件平臺,篩選最優(yōu)引物組合。【結(jié)果】34對引物對中國Psa擴增效果均良好,其中TR14與TR11II、TR19與Psa-01引物序列相同;TR8與Psa-08、TR39II與Psa-10、GM-1834與TR10I、GM-1553與TR64II、TR19Psa-01與TR19II擴增同一TR;Psa-09擴增產(chǎn)物串聯(lián)重復單元長度不唯一,TR2II擴增產(chǎn)物側(cè)翼變異較大,不能通過電泳確定串聯(lián)重復數(shù);最終確定SI值與全部引物組合相同的最低引物數(shù)量為9對,使用該9對引物的組合可將Psa已知的5種生物型準確分開。【結(jié)論】TR23/Psa-04、Psa-03、Psa-05、Psa-06、TR10IGM-1834、TR30I、TR1II、Psa-10TR39II、TR64IIGM-1553等9對引物可代表當前文獻報道的34對引物,進行Psa分型研究,探索獼猴桃潰瘍病的傳播和流行規(guī)律,為病害防控策略的制定提供科學依據(jù)。

關(guān)鍵詞:丁香假單胞菌獼猴桃致病變種;多位點串聯(lián)重復序列分析;群體遺傳結(jié)構(gòu);引物;篩選

中圖分類號:S663.4;S436.634 文獻標志碼:A 文章編號:1009-9980(2024)06-1188-11

Screening and validation of MLVA typing primers for the Pseudomonas syringae pv. actinidiae

YAO Ling1, WANG Hai2, HUANG Lu1, AN Xingyu1, CHEN Wen1, WANG Lishuang1, XUE Yuan3, WU Shiping1*

(1Institute of Plant Protection, Guizhou Academy of Agricultural Sciences/Key Laboratory of Crop Genetic Resources and Germplasm Innovation in Karst Mountains Ministry of Agriculture and Rural Affairs, Guiyang 550006, Guizhou, China; 2Institute of Agricultural Science and Technology Information, Guizhou Academy of Agricultural Sciences, Guiyang 550006, Guizhou, China; 3Anshun Branch of Guizhou Tobacco Company, Anshun 561000, Guizhou, China)

Abstract: 【Objective】 Kiwifruit canker caused by Pseudomonas syringae pv. actinidiae (Psa), is one of the most threatening diseases in the kiwifruit industry. Studying the population genetic structure of Psa can provide theoretical reference for scientific prevention and control of this disease. The multiple-locus variable-number tandem-repeats analysis (MLVA) has been reported to study the population genetic structure of Psa. At present, there are problems with inconsistent and excessive primers in the analysis of the genetic structure of Psa population using MLVA technology. Using too many primers will make MLVA typing technology lose its advantages like convenience and low cost. In order to screen primer combinations suitable for studying the population genetic structure of Psa, 34 pairs of primers reported were analyzed. 【Methods】 To verify the amplification efficiency of primers on Chinese Psa, we used 34 pairs of primers to amplify 10 strains of Psa isolated and preserved in our laboratory. We downloaded the whole genome data of 127 Psa strains from Genbank for primer screening. We then used 34 pairs of primers on the genome sequences of these 127 Psa strains to perform Simulated PCR to obtain TR data. Calculate MLGs and SI using “popper” package to evaluate the typing ability of each primer with Simpson index (SI) as the standard for screening primer combinations, develop a program code using R to calculate the SI of typing results for different primer combinations, and use the df2genind() function of the “poppr” package to convert the simulated PCR result data into genind format. Primer combination SI calculation was performed by using the diversity_stats [mlg.table()] function, starting from the SI of the typing results of 2 pairs of primer combinations, and then calculating 3 pairs of primer combinations until the SI of the calculated primer combination was equal to the SI of all primers. This primer combination was the optimal primer combination. Use the genotype_curve() function of the “poppr” package to statistically analyze the multi locus genotypes (MLGs) of Psa for all primer combinations; and using the entire genome sequences of 20 and 10 Psa strains, a UPGMA clustering tree was constructed using the bruvo.boot() function based on the selected primer combinations to verify the typing effect of the selected primer combinations. 【Results】 34 pairs of primers had good amplification efficiency for Psa in China. By analyzing the results of simulated PCR data, it was found that TR14 and TR11II, TR19 and Psa-01 had the same sequence. TR8 and Psa-08, TR39II and Psa-10, GM-1834 and TR10I, GM-1553 and TR64II, TR19Psa-01 and TR19II amplified the same TR. The TR unit length of Psa-09 amplification product was not unique and the lateral variation of TR2II amplification product was large, which was not determining TRs by electrophoresis. By calculating the MLGs of each primer typing result, it was found that 34 pairs of primer MLGs were between 2-20. Among them, TR10Ⅰ, GM-1834, TR39Ⅱ, and Psa-10 had the highest MLGs of 20, while TR15I, TR17 and TR22 had the lowest MLGs of 2; By calculating the SI of each primer typing result, it was found that the SI values of 34 pairs of primers ranged from 0.015 4 to 0.896 8, with TR10Ⅰ, GM-1834 having the highest SI value of 0.896 8 and TR15I having the lowest SI value of 0.015 4. Through the program developed by R, it was found that the SI value of different primer combination typing results using all primer combinations was 0.984 7. The combination of two pairs of primers with the highest SI was Psa03 and GM-1834TR10I, with an SI value of 0.973 6, which did not reach the SI value of all primers. The combination of three pairs of primers with the highest SI was Psa03, GM-1834TR10I, and TR39IIPsa10, with an SI value of 0.980 3, which still did not reach the SI value of all primers. The primer combinations with the same SI values as all primers were TR23/Psa-04, Psa-03, Psa-05, Psa-06, TR10IGM-1834, TR3II, TR1II, Psa-10TR39II and TR64IIGM-1553, among which TR23 and Psa04 can be replaced with each other, and you can choose one of them. The MLGs of the 9 primers typing results were equal to the MLGs of all primer typing results, UPGMA cluster tree analysis found that 9 pairs of primer combinations can accurately separate the 5 biovar of Psa, and some differences within the biovar 3 can be seen. 【Conclusion】 The above results indicated that using a combination of these 9 primers for typing analysis had the same effect as using all primers. After verification, the combination of 9 pairs of primers can accurately separate the 5 biovars of Psa. The combination of 9 pairs of primers including TR23/Psa-04, Psa-03, Psa-05, Psa-06, TR10IGM-1834, TR3II, TR1II, Psa-10TR39II and TR64IIGM-1553, can be used to study the population genetic structure of Psa, explore the transmission and prevalence patterns of kiwifruit canker disease, and provide scientific basis for the formulation of disease prevention and control strategies.

Key words: Pseudomonas syringae pv. actinidiae; Multiple loci variable number of tandem repeats analysis; Population genetic structure; Primer; Screen

丁香假單胞菌獼猴桃致病變種(Pseudomonas syringae pv. actinidiae,Psa)引起的獼猴桃細菌性潰瘍病嚴重影響獼猴桃產(chǎn)業(yè)發(fā)展[1],該病害發(fā)生前期隱蔽性強,不易發(fā)現(xiàn),且傳播迅速、感染植株死亡率高,防治極其困難[2-3]。全國各獼猴桃產(chǎn)區(qū)均受到獼猴桃潰瘍病的危害,受害嚴重園區(qū)發(fā)病率超過80%,甚至全園發(fā)病導致毀園[4-6]。近年來,各國研究者通過指紋圖譜、多位點序列分析和全基因組序列分析等方法將Psa分為5種不同的生物型(biovar),分別為biovar 1、2、3、5和6。其中biovar 1最早在日本發(fā)現(xiàn),意大利也曾有零星發(fā)現(xiàn);biovar 5和6僅在日本發(fā)現(xiàn);biovar 2僅在韓國發(fā)現(xiàn);biovar 3為全球流行群體,其群體遺傳結(jié)構(gòu)十分復雜[7],中國截至目前所分離到的Psa均屬于biovar 3。對Psa群體結(jié)構(gòu)和分布特征開展系統(tǒng)分析有助于認識獼猴桃潰瘍病的傳播和流行趨勢,為病害防控策略的制定提供科學依據(jù)[8-10]。

多位點可變數(shù)目串聯(lián)重復序列分析(multiple loci variable number of tandem repeats analysis,MLVA)廣泛應用于醫(yī)學病原細菌及植物病原細菌群體遺傳結(jié)構(gòu)研究,具有成本低、分辨率高、數(shù)據(jù)易于整合、通量高等優(yōu)點[11],Osanloo等[12]采用ERIC-PCR分型方法和MLVA分型方法對鮑曼不動桿菌開展分型研究,使用rep-PCR分型方法將伊朗100株鮑曼不動桿菌分為4個類群,MLVA分型方法則分為9個類群,表明MLVA技術(shù)分辨率較ERIC-PCR更高;Siarkou等[13]采用MLST分型和MLVA分型方法對流產(chǎn)衣原體進行了分型研究,發(fā)現(xiàn)MLST將流產(chǎn)衣原體分為6個類群,MLVA技術(shù)則分為7個類群,表明MLVA分型技術(shù)的分辨率高于MLST。已有研究者采用此方法對Psa群體遺傳結(jié)構(gòu)進行了研究,Ciarroni等[14]設(shè)計了13對MLVA引物,對142株P(guān)sa進行群體遺傳結(jié)構(gòu)研究,發(fā)現(xiàn)來自中國、日本、新西蘭和法國等不同國家或地區(qū)的142株P(guān)sa可分為10個不同的亞群,并發(fā)現(xiàn)中國的Psa菌株具有廣泛的遺傳多樣性;Cunty等[15]設(shè)計了11對MLVA引物對340株P(guān)sa的群體遺傳結(jié)構(gòu)進行了分析,發(fā)現(xiàn)中國Psa具有豐富的遺傳多樣性;趙志博等[16]設(shè)計了10對MLVA引物用以建立中國Psa群體遺傳結(jié)構(gòu)分型技術(shù),并應用于來自貴州修文縣7個代表性果園62株P(guān)sa群體結(jié)構(gòu)研究中,發(fā)現(xiàn)62株P(guān)sa可分為3個不同的亞群。至此,MLVA引物數(shù)量多達34對。使用過多MLVA引物會使該技術(shù)失去低成本和便捷的優(yōu)勢。筆者在本研究中對已報道的MLVA引物進行篩選和分析,力求減少引物的使用而不降低分型效果,篩選出可以精準快速地進行Psa分型的引物組合。該引物組合可用于Psa群體遺傳結(jié)構(gòu)研究,探索Psa的傳播和流行規(guī)律,為獼猴桃潰瘍病防控策略的制定提供科學依據(jù)。

1 材料和方法

1.1 MLVA引物PCR擴增效率驗證

1.1.1 MLVA引物 MLVA引物如表1所示。

1.1.2 供試菌株 挑選10株具有代表性的Psa菌株驗證34對引物對中國菌株的擴增效率(表2)。

1.1.3 PCR、電泳條件 PCR條件:95 ℃ 3 min,95 ℃ 30 s,退火溫度30 s,72 ℃ 1.5 min,35個循環(huán),72 ℃ 5 min,最后保持12 ℃(表1);毛細管電泳采用安捷倫科技有限公司生產(chǎn)的毛細管電泳儀,試劑采用DNF900試劑盒;毛細管電泳程序設(shè)置:5.0 kV 30 s,5.0 kV 10 s注入Marker,5.0 kV 10 s注入樣品及Ladder,最后5.0 kV運行80 min。

1.2 模擬PCR篩選MLVA引物

以Genbank中下載127株P(guān)sa全基因組序列為模板,表1所列引物對為引物,使用SPCR 3.0進行模擬PCR,模擬PCR參數(shù)為:Up Threshold:0.8;Down Threshold:0.8;Pa Threshold:0.8;Max Product:500 bp;Min Product:35 bp(其中Psa-09 Max Product設(shè)置為1000 bp)[26]。

1.3 數(shù)據(jù)分析

1.3.1 串聯(lián)重復數(shù)(TRs)計算 將模擬PCR擴增結(jié)果的長度信息導入Excel中,整理后按照下列公式進行串聯(lián)重復數(shù)(tandem repeats,TRs)的計算,統(tǒng)計引物的擴增情況。

[串聯(lián)重復數(shù)=序列長度-側(cè)翼長度重復單元長度]。

1.3.2 引物組合篩選 以辛普森指數(shù)(Simpsons index,SI)作為篩選引物組合的標準,計算所有引物組合的SI,并根據(jù)SI的大小篩選引物組合[27]。基于R version 4.0.2開發(fā)程序進行引物組合的篩選,采用poppr軟件包的df2genind()函數(shù)將模擬PCR結(jié)果矩陣轉(zhuǎn)化為genind格式,利用diversity_stats [mlg.table()]函數(shù)進行引物組合SI的計算,從2對引物組合的SI開始計算,然后計算3對引物組合的SI,直到所計算引物組合的SI等于全部引物組合下的SI,該引物組合即為最優(yōu)引物組合[28]。

1.3.3 引物組合效果驗證 采用poppr軟件包的genotype_curve()函數(shù)對所有的引物組合下Psa的多位點基因型數(shù)(Multilocus genotypes,MLGs)進行統(tǒng)計;以10株P(guān)sa的TR數(shù)據(jù)結(jié)合Genbank下載20株P(guān)sa全基因組序列(表2),采用bruvo.boot()函數(shù)基于篩選獲得的引物組合構(gòu)建UPGMA聚類樹,驗證所篩選引物組合的分型效果[29]。

2 結(jié)果與分析

2.1 PCR擴增效果驗證

除TR10I、TR14I、TR15I、TR30I等4對引物外,Psa-10(見圖1左)、TR2、TR5等30對引物對供試的10個Psa菌株均能擴增出清晰明亮的單一條帶,進一步分析發(fā)現(xiàn),TR10I(見圖1右)、TR14I、TR15I、TR30I等4對引物的下游引物采用反向互補序列后可擴增出單一清晰條帶。結(jié)果表明34對引物均對供試Psa菌株表現(xiàn)良好擴增效果,詳細結(jié)果見表3。

2.2 模擬PCR

模擬PCR結(jié)果如表3所示,TR2等10對引物能將127株P(guān)sa完全擴增成功,GM-1834等22對引物擴增的菌株數(shù)大于105株,Psa-09和TR23引物擴增的菌株數(shù)最少,分別為59株和98株。

通過對模擬PCR擴增的序列文件分析,TR8與Psa-08、TR39II與Psa-10、GM-1834與TR10I、GM1553與TR64II、TR19Psa-01與TR19II擴增同一TR;Psa-09 TR長度不固定,TR2II側(cè)翼長度變異較大,不能通過電泳準確推斷TR數(shù)。將序列相同的引物、擴增同一TR的引物僅保留1對,不能通過電泳判斷TRs的引物被剔除,剩余25對引物進行后續(xù)的分析。

25對引物擴增的產(chǎn)物長度、多位點基因型數(shù)(MLGs)、辛普森指數(shù)(SI)結(jié)果各不相同。從MLGs來看TR10I、GM-1834、Psa-10和TR39II等4對引物擴增的MLGs最多,為20個;TR15I、TR17和TR22等3對引物擴增的MLGs最少,為2個;從SI來看,TR39IIPsa-10、TR10I、GM-1834和Psa-03等4對引物擴增基因型的SI較高,分別為0.896 8、0.878 9、0.878 9和0.735 3;TR15I、TR30I、GM-4076和TR3II等4對引物擴增基因型的SI較低,均小于0.3。25對引物中,GM-254擴增的MLGs較多,為9,其SI為0.356 2,均勻度較低;TR17和TR22擴增的MLGs較少,為2,SI為0.478 1,均勻度較高(表4)。

2.3 引物組合篩選

使用R進行25對引物所有組合的查找及SI值的計算結(jié)果表明:選擇25對引物時,其組合僅有1個,SI值為0.984 7;選擇9對引物時,引物組合有2 042 975個,其SI值最大的前3個組合的SI值分別為0.984 7、0.984 7和0.984 5,最大SI值與25對引物的SI值相同。選擇9對以上引物組合時,其最大SI值也達到了0.984 7,最大SI值未隨引物增加而增加(表5、圖2)。從MLGs來看,使用2對引物組合時最大MLGs為65,使用9對引物組合最大MLGs與25對引物的MLGs相同,均為99。

以上結(jié)果表明,使用TR23/Psa-04、Psa-03、Psa-05、Psa-06、TR10IGM-1834、TR30Ⅰ、TR1II、Psa-10TR39II、TR64IIGM-1553等9對引物的組合可以達到25對引物的效果,其中TR23和Psa-04可以相互替換,任選其一使用即可。

2.4 引物組合分型效果驗證

獲得的9對引物組合可將Psa的5種生物型(biovar)準確分開;10株代表性Psa均為biovar 3,其中GZCC7520447和GZCC7520448來自烏當區(qū)偏坡鄉(xiāng),獨立聚為一支;GZCC7520193和GZCC7520192均來自修文縣六桶鄉(xiāng),以相近的遺傳距離聚在一起;GZCC7520186和GZCC7520161均來自修文縣,以相近的遺傳距離聚在一起;biovar 3菌株間存在一定差異(圖3)。上述結(jié)果表明,所獲得的9對引物組合可用于Psa群體遺傳結(jié)構(gòu)研究。

3 討 論

各國學者采用MLVA技術(shù)開展Psa群體遺傳結(jié)構(gòu)研究共設(shè)計了34對MLVA引物[14-16],34對引物中,有些是相同序列(TR14=TR11Ⅱ、TR19=Psa-01);有些是擴增同一TR(TR8與Psa-08、TR39Ⅱ與Psa-10、GM1834與TR10Ⅰ、GM1553與TR64Ⅱ、TR19Psa-01與TR19II);有些序列(TR10I、TR14I、TR15I、TR30I)不能直接被引用,Mazzaglia等[30]的研究中也提到了該不足。有必要針對該34對引物開展系統(tǒng)的分析和篩選,以獲得一組可以直接使用、快速精準地對Psa進行分型分析的引物組合。

筆者在本研究中在不降低分辨率的前提下進行MLVA引物組合的篩選,將34對引物減少到只需9對(TR23/Psa-04、Psa-03、Psa-05、Psa-06、TR10IGM-1834、TR30I、TR1II、Psa-10TR39II、TR64IIGM-1553),大大降低了研究的時間和資源成本。該9對引物的組合經(jīng)驗證可準確、快速地對Psa進行分型分析,進行Psa群體遺傳結(jié)構(gòu)研究,探索Psa傳播和流行規(guī)律,為獼猴桃潰瘍病防控策略的制定提供科學依據(jù)。

筆者在本研究中需查找引物的所有組合并計算SI值,計算量達百萬級以上。Optimal Combination Finder (OCF)是一個專門用來找出引物所有可能的組合,并進行引物所有可能組合的SI計算的程序[18]。但由于其操作比較復雜,非開發(fā)者很難自行利用該程序進行引物組合的查找和SI的計算,因此筆者基于R開發(fā)了一段計算程序,進行所有可能引物組合的查找和SI的計算,它是利用R編寫并依托于poppr軟件包使用。R語言平臺使用方式簡單快捷,可多線程運行,提高計算速度,直接采用poppr軟件包計算SI值則大大簡化了計算步驟,如筆者在本研究中所有引物組合的SI值的計算僅需幾個小時便可以完成,這極大地提高了引物組合篩選的效率。該計算程序可以應用于其他微生物MLVA引物的篩選。

筆者在本研究中所引用的34對引物對127株P(guān)sa菌株的全基因組擴增信息中,存在部分引物擴增不出條帶的情況,但整體來說,供試引物對大多數(shù)菌株能擴增出條帶,僅Psa-09和TR23引物能擴增出條帶的菌株數(shù)量較少。不能擴增出條帶的原因可能是:(1)菌株序列中本身不存在此位點;(2)GenBank中下載的127株P(guān)sa全基因組序列中有118株未組裝,未組裝的Psa菌株的全基因組信息由幾十到幾百條序列組成,如果序列截斷的位置剛好是位點所在,模擬PCR便無法擴增。無法準確判斷擴增不出條帶的原因,若將缺失信息的菌株舍棄,樣本量將會大大減少,不利于引物組合的篩選。其他的研究者在面對缺失信息時,一般是使用字符將其標記出來,如:Ikawaty等[31]使用“999”表示PCR無擴增信息;Concei??o等[32]使用“99”表示未獲得PCR擴增信息;Ciarroni等[14]使用“-1”來表示擴增信息的缺失。筆者在本研究中將缺失信息統(tǒng)一使用“0”表示,一方面便于SI的計算,另一方面也使所有菌株都參與到了引物組合的篩選中,獲得了適用于Psa群體遺傳結(jié)構(gòu)研究的引物組合。

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收稿日期:2023-10-19 接受日期:2023-11-09

基金項目:貴州省科技計劃項目(黔科合基礎(chǔ)[2019]1308號)

作者簡介:姚令,男,研究實習員,碩士,研究方向為植物病理學。E-mail:1158142736@qq.com

*通信作者 Author for correspondence. E-mail:gzusp@126.com

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