Skip to main content
Advertisement
Browse Subject Areas
?

Click through the PLOS taxonomy to find articles in your field.

For more information about PLOS Subject Areas, click here.

  • Loading metrics

Screening nested-PCR primer for ‘Candidatus Liberibacter asiaticus’ associated with citrus Huanglongbing and application in Hunan, China

  • Yanyun Hong ,

    Contributed equally to this work with: Yanyun Hong, Yongyang Luo, Jianglan Yi

    Roles Conceptualization, Data curation, Formal analysis, Funding acquisition, Writing – original draft

    Affiliation Hunan Provincial Key Laboratory for Biology and Control of Plant Pests, College of Plant Protection, Hunan Agricultural University, Changsha, Hunan province, China

  • Yongyang Luo ,

    Contributed equally to this work with: Yanyun Hong, Yongyang Luo, Jianglan Yi

    Roles Data curation, Writing – original draft

    Affiliation Hunan Provincial Key Laboratory for Biology and Control of Plant Pests, College of Plant Protection, Hunan Agricultural University, Changsha, Hunan province, China

  • Jianglan Yi ,

    Contributed equally to this work with: Yanyun Hong, Yongyang Luo, Jianglan Yi

    Roles Conceptualization, Formal analysis, Investigation

    Affiliation College of life Science and Technology, Beijing University of Chemical Technology, Beijing, China

  • Ling He ,

    Roles Investigation

    ‡ These authors also contributed equally to this work.

    Affiliation Hunan Provincial Key Laboratory for Biology and Control of Plant Pests, College of Plant Protection, Hunan Agricultural University, Changsha, Hunan province, China

  • Liangying Dai ,

    Roles Supervision, Visualization

    ‡ These authors also contributed equally to this work.

    Affiliation Hunan Provincial Key Laboratory for Biology and Control of Plant Pests, College of Plant Protection, Hunan Agricultural University, Changsha, Hunan province, China

  • Tuyong Yi

    Roles Conceptualization, Funding acquisition

    yituyong@hotmail.com

    Affiliation Hunan Provincial Key Laboratory for Biology and Control of Plant Pests, College of Plant Protection, Hunan Agricultural University, Changsha, Hunan province, China

Abstract

Citrus Huanglongbing (HLB) is one of the most devastating citrus diseases worldwide. Sensitive and accurate assays are vital for efficient prevention of the spread of HLB-associated “Candidatus Liberibacter spp”. “Candidatus Liberibacter spp” that infect Citrus includes “Candidatus Liberibacter asiaticus” (Las), “Candidatus Liberibacter africanus” (Laf) and “Candidatus Liberibacter americanus” (Lam). Of them, Las is the most widespread species. In this study, a set of nested PCR primer pairs were screened to diagnose Las, and the nested PCR method greatly enhanced the sensitivity to detect Las up to 10 times and 100 times compared to qPCR and conventional PCR, respectively. Totally, 1112 samples from 5 different citrus cultivars in 39 different counties and cities were assayed by nested PCR. The results show that 384 samples were HLB-infected; the highest positive detection rate was 79.7% from the lopsided fruit samples, and the lowest positive detection rate was 16.3% from the apical dieback samples. The results indicate that the designed nested PCR primer pairs can detect Las from different symptomatic tissues, different citrus cultivars and different geographic regions. The set of nested PCR primers designed in the present study will provide a very useful supplementation to the current approaches for Las detection.

Introduction

Citrus Huanglongbing (HLB), also known as citrus greening, has been one of the most devastating diseases to threaten the citrus industry in Asia, Africa and America [1]. The citrus trees acutely infected by HLB show yellow shoots, foliar blotchy mottle that may be similar to the symptom of zinc deficiency, vein corking that may be identical to the symptom by the infection of Citrus Tristeza virus, poor flowering and stunting [2]. The citrus trees chronically infected with HLB are sparsely foliated, display extensive twig or limb die-back and will eventually die within three to five years [3, 4]. The yield of HLB-infected citrus is reduced by 30% to 100%, and the fruit quality is degraded [1, 2, 5]. It was reported that HLB may reduce Texas citrus production by 20% ($140 million) after 2 years and up to 60% after 5 years of infection [1]. HLB is caused by ‘Candidatus Liberibacter spp’, which are gram-negative, unculturable, phloem-limited organisms that belong to α subdivision of the Proteobacteria. HLB-associated Candidatus Liberibacter spp include “Candidatus Liberibacter asiaticus” (Las), “Candidatus Liberibacter africanus” (Laf) and “Candidatus Liberibacter americanus” (Lam) [3]. Las is the most widespread species and is responsible for the main increasing economic losses [6, 7]. HLB was transmitted by budding, dodder, grafting and the psyllid vectors. HLB is spread very fast that the spread distance could reach 193 km (120 miles) per year [8, 9]. Unfortunately, currently, there is no effective curative treatment to control this disease, and no cultivars are resistant to this pathogen. Controlling the insect vector and removal of the infected trees are the most general control measures in HLB management. Therefore, sensitive and accurate diagnosis is a prerequisite to research and manage HLB.

Due to that HLB bacteria could not be cultured, Koch's postulates on HLB were not performed [10]. Meanwhile, HLB-infected citrus lacking specific symptoms or that was asymptomatic during the incubation period resulted in some false-negative diagnoses based on visual symptoms [4]. Currently, many molecular detection assays based on PCR, including conventional PCR [11, 12], SSR [13, 14], droplet digital PCR [15], LAMP[16, 17], immune capture-PCR[18], qPCR [4, 19] and nested PCR [20], have been used to detect HLB-associated bacteria. Nested PCR, whose products of the first round of PCR are diluted and used as the template for the second round of amplification, has been proven to have higher sensitivity than other molecular detection assays in diagnosing diseases[2123] such as HLB[24, 25]. Thus, the nested PCR was used in this study.

Many types of genomic loci have been used as molecular markers in the detection of HLB. For example, the 16S rRNA gene rplKAJL-rpoBC cluster region, intergenic 16S/23S rRNA gene spacer region, bacteriophage-type DNA polymerase region, 18S rRNA gene and the outer membrane protein (OMP) gene were widely used in the molecular detection of HLB [15, 2527]. However, it was noticeable that molecular detection assays were subject to false negative results owing to uneven distribution of the HLB bacteria in citrus and even among cells within discrete tissues, yielding both positive and negative samples from the same citrus tree. Moreover, the same HLB bacteria species had significant differences among various geographic locations, and the same HLB bacteria species had no significant difference among different citrus cultivars [27, 28]. Therefore, it is important to choose an appropriate assay method and a proper genomic locus to detect the suspicious HLB samples from a particularly geographical location. The OMP (outer member protein) gene of Candidatus Liberibacter asiaticus, with 2,346 bp of nucleotides, was first sequenced in 2005[29]. The three-dimensional structures of OMP were highly conserved, and the nucleotide sequences of the OMP gene showed very high similarity among isolates (99%) and high species specificity (99%) [29, 30]. In this study, OMPs and nested PCR were used as target genes and the detection assay method, respectively, to detect HLB- suspicious samples collected from Hunan province in China.

Materials and methods

Ethics statement

The research complied with protocols approved by the plant protection and plant inspection station of Hunan Province, China, and abided by the legal requirements of China. The research was conducted according to plant protection regulations.

Sample sources and DNA preparation

From 2014 to 2017, 1112 citrus tissue samples, including 154 lopsided fruits in green in color and 958 leaf samples that 422 showed blotchy leaves citrus, 389 showed yellow shoots, 147 showed apical dieback, were collected from 5 different citrus cultivars in 39 different counties and cities that covered almost all citrus cultivars and planting areas in Hunan province, China(East Longitude:109°68′-113°96′;North Latitude: 24°97′-29°48′) (Table 1 and Fig 1). All samples were collected and sent to us by concern counties plant protection station (S1 Table).Leaves and fruits were washed with running tap water and blotted dry with paper towels. The midribs and fruit peels were excised. Then, 100 mg of each sample were ground in liquid nitrogen, and DNA was extracted using the CTAB method as previously described [31]. The extracted DNA was dissolved in 50 μl of TE buffer. The quality and concentration of DNA were checked by a NanoDrop ND-2000 (NanoDrop Technologies Inc., Wilmington, DE, USA)[32,33].

thumbnail
Fig 1. Map of Hunan Province, China with red dots indicating locations where the studied samples were collected.

https://doi.org/10.1371/journal.pone.0212020.g001

thumbnail
Table 1. Information of the collected samples including the locations, symptoms and numbers.

https://doi.org/10.1371/journal.pone.0212020.t001

Primers design

Two sets of primers were designed for the nested PCR to amplify the conserved region of BamA that encodes OMP assembly factor and is annotated as a single copy in the Las genome (Accession No: JQ928882.1) [3436]. The optimum inner and qPCR primers were designed using Beacon Design Software v7.0 (Premier Biosoft International, CA, USA) with the following criteria: GC %≥40–50, Tm = 60 ±2°C, and primer length = 18–22 bp. To ensure amplification efficiency, among the designed primers that had the least possibility in forming a hairpin, self/cross dimer structures were selected for further validation. For designing the outer primers, the same criteria were applied, except that a longer amplicon size (i.e., 1000–1500 bp) was designed. At the same time, the conventional PCR primer OI1 /OI2 and S3/S4 were obtained from previous study [12]. Three sets of nested PCR primers were validated (F1/B1 and F3/B3; F2/B2 and F3/B3; OI1/OI2 and S3/S4). To identify these pathogenic microorganisms used in validation the specificity of designed nested-PCR primers indeed existed in those DNA samples, Xac1/Xac2 (Accession No: KY849808.1), Spir1/Spir2 (Accession No: KT377378.1), Citrus actin(Accession No: XM_006464503.3) and Potato actin(Accession No: X55749.1) were designed according to the same criteria. All the primers were synthesized by Sangon Biotech (Shanghai) Co., Ltd. All the primers information are displayed (Table 2).

Validation the specificity of designed nested-PCR primers

To validate the nest-PCR primer specificity, we firstly BLAST all primers against citrus and Asian citrus psyllid (ACP) sequences. To ensure that the designed primers were specific for Las, the specificities of the outer and inner primers(F1/B1 and F3/B3) were evaluated by nested-PCR using DNAs extracted from other citrus-related pathogens, such as Xanthomonas citri subsp and Spiroplasma citri preserved in our laboratory. Moreover, three DNAs of Laf, Lam and “Ca. L. solanacearum” generous gifted by the “Citrus Research Institute Chinese Academy of Agricultural Science” were also used for specificity evaluation. To identify these pathogens in those DNA samples, special primers OI1 + OA1+ OI2c, described by Jagoueix et al (1996), were used to amplify Laf and Lam; primers ZCf/OI2c were used to amplify Ca. L. solanacearum, primers Xac1/Xac2 were used to amplify Xanthomonas citri subsp; primers Spir1/Spir2 were used to amplify Spiroplasma citri. At the same time, Citrus and potato actin gene as plant control were amplified. Objective genes were confirmed by electrophoresis in 1.2% agarose gels and sequencing PCR products and BLAST them online (Table 2 and S1 Appendix). To confirm whether the locus sequence is conserved and shared among “Candidatus Liberibacter asiaticus” isolates, seven DNAs of Las, which were collected in Hunan, Guangdong, Fujian, Jiangxi, Yunnan, Sichuan and Guangxi provinces and stored at“Citrus Research Institute of Hunan”, were tested using the nested PCR primers(F1/B1 and F3/B3) in this study. PCR products were separated by electrophoresis in 1.2% agarose gels and detected after staining with ethidium bromide.

Validation of the sensitivity of nested-PCR

Usually, the determination of primer sensitivity was based on different templates or different concentrations of same template. Firstly, five suspected samples were amplified by nested PCR primer pairs (F1/B1 and F3/B3) and conventional PCR primer (OI1/OI2). Then we detected the concentration of the conventional PCR positive product and nested PCR positive product from Fig 2A or 2B lane 5 by a NanoDrop ND-2000, and adjusted to 100 ng/μl as the dilution template. The PCR product was serially diluted in a range of 1, 10, 102, 103, 104 and 105, which represented 105 to 1 pg/μl Las DNA, and served as the templates to evaluate the sensitivity among nested PCR, conventional PCR and qPCR. The PCR product from 2A line 5 was diluted as the template for conventional PCR (Fig 2C) and the PCR product from 6B line 5 was diluted as the templates for the nested PCR (Fig 2D) and qPCR. To evaluate the amplification efficiency of qPCR, Las DNA (Fig 2B) serially diluted in a range of 10, 102, 103, 104 and 105 served as the templates. The nested PCR mixture (20 μl) was prepared using 2×Easy Taq PCR SuperMix (Transgen Biotech, Beijing, China), and amplification was proceeded using the following parameters: 94°C for 5 min followed by 25 cycles at 94°C for 30 s, 58°C for 30 s and 72°C for 70 s for the first round of PCR and 35 cycles at 94°C for 30 s, 62°C for 30 s and 72°C for 30 s for the second round of PCR. The qPCR mixture (20 μl) was prepared using Trans Start Top Green qPCR SuperMix (Transgen Biotech, Beijing, China), and amplification was proceeded using the following parameters: 94°C for 30 s and followed by 40 cycles at 94°C for 5 s and 60°C for 30 s, and followed by a melt curve (60°C to 90°C, 0.3°Cs-1). At the same time, 2×Easy Taq PCR SuperMix was used in conventional PCR assays. All PCR mixtures (20 μl) included 1 μl of DNA and 20 pmol of primer pairs. Conventional PCR amplification was performed according to early literature [12]. DNA-free H2O citrus was amplified as negative controls. Nested PCR and conventional PCR products were separated by electrophoresis in 1.2% agarose gels and visualized after staining with ethidium bromide. When the Ct value was less than 36, the DNA sample was identified as HLB-infected.

thumbnail
Fig 2. Electrophoretic comparisons of PCR products from conventional and nested PCR and dilution series analyses.

A- conventional PCR of five different samples; B-nested PCR of the same five samples as shown in A; C-conventional PCR of 105 fold dilution series of PCR product shown in Fig 2A-lane 5 and D-nested PCR of dilution series of PCR product shown in Fig 2-B-lane 5. (Marker: 2000bp, 1000bp, 750bp, 500bp, 250bp, 100bp).

https://doi.org/10.1371/journal.pone.0212020.g002

Results

Primers selected for nested-PCR detection system

Three sets of nested PCR primers produced the target products without primer dimers. However, the primers F1/B1 and F3/B3 gave the strongest bands compared to the other two sets of primers according to electrophoresis results (Fig 3). Therefore, the primers F1/B1 and F3/B3 were selected for this study (Table 2). The amplification products are 1318 bp in length for the outer primers and 447 bp in length for the inner primers.

thumbnail
Fig 3. The electrophoresis results of products of three pairs of nest-PCR using four DNA samples, which included two lopsided fruits and one yellow shoot and one blotchy leaf.

+, DNA of Las; -, Negative controls; 1 and 2, lopsided fruits; 3, yellow shoot; 4, blotchy leaf. Each picture was a pair of primer. A, F1/B1; B, F2/B2; C, OI1/OI2; D, F3/B3; E, F3/B3; F, S3/S4. (Marker: 2000bp, 1000bp, 750bp, 500bp, 250bp, 100bp).

https://doi.org/10.1371/journal.pone.0212020.g003

Validation of nested-PCR primer specificity

To validate the nest-PCR primer specificity, we firstly BLAST all primers against citrus and Asian citrus psyllid (ACP) sequences, the results showed all primers had regions with 100% identity to some citrus gene sequences and ACP gene sequences, but showed very low coverage (52–75%) to citrus and ACP gene sequences. For example, F1 was 68% coverage to Citrus sinensis methionyl-tRNA formyltransferase and B1 was 60% coverage to Citrus sinensis fasciclin-like arabinogalactan protein 17, F1 was 52% coverage to citrus psyllid sarcoplasmic reticulum histidine-rich calcium-binding protein-like and B1 was 59% coverage to citrus vacuolar protein sorting-associated protein 37A-like. Then we sequenced the products of the nested-PCR, and BLAST these gene fragments against Citrus sequences and ACP sequences and microbial sequences. The results showed no other homologous sequences except Las—related genes sequence were found, suggesting the set of primers was specific to Las(S2 Appendix). According to the results of electrophoresis and BLAST online, all pathogenic bacteria/fungi (Las, Laf, Lam, Ca. L. solanacearum, Xanthomonas citri subsp, Spiroplasma citri) indeed existed in DNA samples (Fig 4 and S1 Appendix).However, the negative results of several other pathogens further confirmed the specificity of nested-PCR primer pairs (Fig 5). The results of Las isolates from different geographical regions, which were determined by F1/B1 and F3/B3, showed positive, confirming that the sequence locus was conserved and shared among these Las isolates (Fig 6).Therefore, the selective primers are species-specific and highly conserved.

thumbnail
Fig 4. The electrophoresis results on pathogens and plants control.

1, Las; 2, Laf; 3, Lam; 4, Ca. L. solanacearum; 5, Xanthomonas citri subsp; 6,Spiroplasma citri; 7, negative control; 8–11 citrus controls corresponding to Laf, Lam, Xanthomonas citri subsp and Spiroplasma citri; 12 potato control corresponding to Ca. L. solanacearum (Marker: 2000bp, 1000bp, 750bp, 500bp, 250bp, 100bp).

https://doi.org/10.1371/journal.pone.0212020.g004

thumbnail
Fig 5. The electrophoresis results on nested PCR primer specificity.

1, Las; 2, Lam; 3,Laf; 4, Ca. L. solanacearum; 5, Xanthomonas citri subsp; 6,Spiroplasma citri.(Marker: 2000bp, 1000bp, 750bp, 500bp, 250bp, 100bp).

https://doi.org/10.1371/journal.pone.0212020.g005

thumbnail
Fig 6. The electrophoresis results of nested PCR pairs (F1/B1 and F3/B3) from different geographic Las strains.

1, Hunan;2,Guangxi;3,Fujian;4,Yunnan;5,Guangdong; 6,Sichuan;7,Jiangxi; 8, negative control (Marker: 2000bp, 1000bp, 750bp, 500bp, 250bp, 100bp).

https://doi.org/10.1371/journal.pone.0212020.g006

Comparison of the sensitivity among different detection methods

According to the results of electrophoresis, with conventional PCR only the sample in lane 5 was detected as Las-infected (Fig 2A); however, with nested PCR all 5 samples were detected as Las infected (Fig 2B). Analysis of the dilution series of the DNA from lane 5 showed that nested PCR (Fig 2D) detected much lower template DNA concentrations than conventional PCR (Fig 2C). The results indicted that the lowest concentration detected by conventional PCR was 1×103 pg/μl, and the lowest concentration detected by nested PCR was 1× 10 pg/μl(Fig 2). When the qPCR CT value was 35, the template DNA concentration was 1×102pg/μl. Accordingly, the primer sensitivity was inversely correlated with the template concentration; the detection system sensitivity order was nested PCR>qPCR> conventional PCR, meaning that the nested PCR was 10 times more sensitive than that of qPCR and 100 times more sensitive that of conventional PCR. The standard curve in this study had an average slope value of -3.31. The amplification efficiency (AE) of qPCR was therefore estimated to be approximately 0.99 based on the equation AE = [10−1/slope−1].

Detection of HLB in the field samples by nested-PCR

In the study, 1111 field samples were assayed by nested PCR. Totally, 384 samples, including 140 blotchy leaves, 98 yellow shoots, 24 apical dieback samples and 122 lopsided fruits, were diagnosed as HLB-infected. The rate of HLB infection was 34.5%. However, the highest positive detection rate was 79.7% in lopsided fruits, and the lowest positive detection rate was 16.3% in apical dieback samples. There were 36.5%, 25.5%, 6.3% and 31.8% positives among the trees diagnosed based on blotchy leaves, yellow shoots, apical dieback samples and lopsided fruits, respectively (Table 3)

thumbnail
Table 3. The results from nested PCR pairs (F1/B1 and F3/B3).

https://doi.org/10.1371/journal.pone.0212020.t003

Discussion

Sensitive and accurate assays are vital for efficient management of the spread of HLB-associated “Ca. Liberibacter spp”. Although HLB has been known for more than a century, “Ca. Liberibacter spp” species were identified to be associated with HLB in the 1970s [37]. “Ca. Liberibacter spp” could not be cultured, making it impossible to use traditional bacteriological methods to diagnose HLB[10]. HLB -infected trees show a lack of specific symptoms or are asymptomatic during the incubation period, and visual detection is not efficient for diagnosis of HLB. Currently, many methods based on PCR have been used to detect HLB infection, such as conventional PCR [3, 11, 12, 38], SSR[13], immune capture-PCR[17]. LAMP[16,39], PCR- RFLPs[28,40], droplet digital PCR[15], TaqMan qPCR[25], qPCR[11,12,41], qRT-PCR[4,23], and nested PCR[19]. Although these methods have worked well in symptomatic samples, they were subject to false negatives because HLB- associated Las may have a low titer and be unevenly distributed in citrus trees and even among cells within discrete tissues, yielding both positive and negative samples from various tissue samples originating from the same citrus tree [12, 42]. Each assay has advantages and disadvantages. Conventional PCR and SSR assays were simple but of low sensitivity and poor repeatability [14]. LAMP assays were simple but had high costs and poor repeatability [16]. The enzyme-linked immunosorbent assay (ELISA) was highly sensitive and target specific [43], but ELISA procedures were very complicated [35]. The qPCR was highly sensitive but had a high cost. These shortcomings are a great obstacle for these methods to practically diagnose HLB. Nested PCR, in which the products of the first round of PCR were diluted and used as the template for the second round of amplification, has been proved to have higher sensitivity than other molecular detection assays in diagnosing diseases [2123]. In the present study, the sensitivity was in the order of nested PCR>qPCR> conventional PCR. All the results are consistent with the viewpoint that nested PCR had a higher sensitivity and was more suitable for the detection of Las with extremely low titers [4446]. Nested RT-PCR has the advantage of improved sensitivity and specificity over conventional RT-PCR. The specificity is improved because two sets of primers are used for nested RT-PCR reactions. The sensitivity is increased because two rounds of PCR are performed in Nested PCR [18, 47, 48]. Ahmad [30] indicated that the efficiency of amplification affected the sensitivity of qPCR. In this study, the efficiency of amplification from qPCR was 99%. The results showed that the efficiency of amplification was not a key factor for the sensitivity of the assay.

The outer membrane protein (OMP) is vital for bacteria to maintain normal structure and function. OMPs are involved not only in exchanges with the external environment but also in interactions between plants and pathogenic bacteria. The three-dimensional structures of OMPs from Las were highly conserved, and the nucleotide sequences of OMPs from Las showed very high similarity and high species specificity (99%) [17, 29, 30]. OMPs have been used as target genes in the detection HLB bacterial assays [2729]. However, previous literatures indicated that OMPs were highly variable among different geographical isolates and were not suitable for the identification for Las [30]. OMPs were often used to produce antigens and to assess the variation among different geographical isolates. In this study, we describe a new HLB diagnosis method using nested PCR to amplify the conserved region of BamA that encodes the outer membrane protein (OMP) assembly factor and represents a single copy in the Las genome. The method greatly enhanced the sensitivity up to 10 times compared to qPCR and 100 times compared to conventional PCR in the detection of Las.

In the present study, 1112 samples from 5 different citrus cultivars in 39 different counties and cities were assayed by nested PCR. The results showed that 384 samples were HLB-infected, and the highest positive detection rate was 79.7% in lopsided fruit samples, and the lowest positive detection rate was 16.3% in apical dieback samples. All the results are consistent with those of earlier studies [49, 50]. The results indicate that the nested PCR primer pairs could detect Las from various different symptomatic tissues and different locations. Therefore, the nested PCR primer pairs are fit for different citrus cultivars and different geographic regions. The set of nested-PCR primers will provide a very useful supplement to the current approaches to Las detection.

Supporting information

S1 Appendix. Information on sequences and BLAST online.

https://doi.org/10.1371/journal.pone.0212020.s002

(DOCX)

S2 Appendix. All primers against citrus and Asian citrus psyllid (ACP) sequences.

https://doi.org/10.1371/journal.pone.0212020.s003

(DOCX)

Acknowledgments

We acknowledge Qi Li for making the map of samples collection; we thank Mr Fu from “Citrus Research Institute Chinese Academy of Agricultural Science” for his generous gifting three DNAs of Laf, Lam and “Ca. L. solanacearum”, Ms Li from “Citrus Research Institute of Hunan” for providing seven samples of Las, which were collected in Hunan, Guangdong, Fujian, Jiangxi, Yunnan, Sichuan and Guangxi provinces, and we thank Dr Liu for modifying the manuscript.

References

  1. 1. Gottwald TR. Current epidemiological understanding of citrus Huanglongbing. Annual Review of Phytopathology. 2010; 48:119–139. pmid:20415578
  2. 2. Bassanezi RB, Montesino LH, Stuchi ES. Effects of Huanglongbing on fruit quality of sweet orange cultivars in Brazil. Eur. J. Plant Pathology.2009; 125:565–572.
  3. 3. Bove´ J. Huanglongbing: a destructive, newly-emerging, century-old disease of citrus. Plant Pathology. 2006; 88:7–37.
  4. 4. Kogenaru S, Yan Q, Riera N, Roper MC, Deng X, Ebert TA, et al. Repertoire of novel sequence signatures for the detection of Candidatus Liberibacter asiaticus by quantitative real- time PCR. BMC Microbio. 2014 Feb 17. http://www.blomedcentral.com/1471-2180/14/39. pmid:24533511
  5. 5. Schwarz RE. Results of a greening survey on sweet orange in the major citrus growing areas of the Republic of South Africa. South African Journal of Agricultural Science. 1967; 10:471–476.
  6. 6. Lin H, Chen C, Doddapaneni H, Duan YP, Civerolo EL, Bai X, et al. A new diagnostic system for ultra-sensitive and specific detection and quantification of Candidatus liberibacter asiaticus, the bacterium associated with citrus Huanglongbing. Journal of Microbiological Methods. 2010; 81(1):17–25. pmid:20096734
  7. 7. Zhang MQ, Duan YP, Zhou LJ, Turechek WW, Powell CA. Screening molecules for control of citrus Huanglongbing using an optimized regeneration system for ‘Candidatus liberibacter asiaticus’ -infected periwinkle (Catharanthus roseus) cuttings. Phytopathology.2010; 100(3): 239–245. pmid:20128697
  8. 8. Gottwald TR, Graça JVD, Bassanezi RB. Citrus Huanglongbing: the pathogen and its impact. Plant Health Progress.2007;
  9. 9. Gottwald TR, Graham JH, eds. Proceedings of the international research conference on Huanglongbing, Orlando. St. Paul, MN: Plant Management. Netw; 2008. pp. 480–491.
  10. 10. Sechler A, Schuenzel EL, Cooke P, Donnua S, Thaveechai N, Postnikova AL, et al. Cultivation of “Candidatus Liberibacter asiaticus,” “Ca. L. africanus,” and “Ca. L. americanus” associated with Huanglong- bing. Phytopathology.2009; 99:480–486. pmid:19351243
  11. 11. Tatineni S, Sagaram US, Gowda S, Robertson CJ, Dawson WO, Iwanami T, et al. In planta distribution of ‘Candidatus Liberibacter asiaticus’ as revealed by polymerase chain reaction (PCR) and Real-Time PCR. Phytopathology. 2008; 98: 592–99. pmid:18943228
  12. 12. Teixeira DC, Saillard C, Couture C, Martins EC, Wulff NA, Eveillard-Jagoueix S, et al. Distribution and quantification of ‘Candidatus Liberibacter americanus’, agent of Huanglongbing disease of citrus in Sao Paulo State, Brazil, in leaves of an affected sweet orange tree as determined by PCR. Molecular and Cellular Probes.2008; 22: 139–150. pmid:18400468
  13. 13. Chen J, Deng X, Sun X, Jones D, Irey M, Civerolo E. Guangdong and Florida populations of ‘Candidatus Liberibacter asiaticus’ distinguished by a genomic locus with short tandem repeats. Phytopathology.2010; 100:567–572. pmid:20465412
  14. 14. Xu MR, Zheng Z, Li XY, Hong HX, Ding XL. Intraspecific genetic diversity analysis of ‘Candidatus Liberibacter asiaticus’ by short tandem repeats and page. Acta Phytopathologica Sinica. 2014;44(6):609–619.
  15. 15. Zhong X, Liu XL, Lou BH, Zhou CY, Wang XF. Development of a sensitive and reliable droplet digital PCR assay for the detection of ‘Candidatus Liberibacter asiaticus’. Journal of Integrative Agriculture.2018; 17(2): 483–487.
  16. 16. Rigano LA, Malamud F, Orce IG, Filippone MP, Marano MR, Do-Amaral A, et al. Rapid and sensitive detection of Candidatus Liberibacter asiaticus by loop mediated isothermal amplification(LAMP) combined with a lateral flow dipstick. BMC Microbio.2014; http://www.blomedcentral.com/1471-2180/14/86 pmid:24708539
  17. 17. Okuda M, Kawano S, Murayama Y, Iwanami T. Conditions for loop-mediated isothermal amplification (LAMP) and a nonmacerating DNA extraction method to assay for Huanglongbing (citrus greening) disease. Annals of the Phytopathological Society of Japan.2008; 74(4):316–320.
  18. 18. Ding F, Paul C, Brlansky R, Hartung JS. Immune tissue print and immune capture-PCR for diagnosis and detection of Candidatus liberibacter asiaticus. Scientific Reports.2017. pmid:28418002
  19. 19. Aghasadeghi MR, Mohraz M, Bahramali G, Aghakhani A, Banifazl M, Foroughi M, et al. Frequency and genotype of hepatitis d virus infection in patients infected with HIV and those undergoing hemodialysis. Hepatitis Monthly.2013. pmid:23914228
  20. 20. Arredondo VR, Delgado OJC, Beltrán BM, Anguiano CJ, Cerna CE, Rodríguez PY,et al. A review of techniques for detecting Huanglongbing (greening) in citrus. Can J Microbiol. 2016, 62(10):803–811. pmid:27590666
  21. 21. Traversa D, Iorio R, Otranto D. Diagnostic and clinical implications of a nested PCR specific for ribosomal DNA of the feline lungworm Aelurostrongylus abstrusus (nematoda, strongylida). Journal of Clinical Microbiology. 2008; 46(5):1811–1817. pmid:18367571
  22. 22. Langeroudi AG, Babakhani NR, Zolfaghari MR, Majidzadeh KA, Morovvati A, Soleimani M. Detection of Coxeilla brunetii in bulk tank milk samples from dairy bovine farms using nested-PCR in Qom, Iran,2011.Iranian Journal of Veterinary Medicine.2013;7(3): 207–211.
  23. 23. Fonseca AJD, Galvão RS, Miranda AE, Ferreira LC, Chen Z. Comparison of three human papilloma virus DNA detection methods: next generation sequencing, multiplex‐PCR and nested‐PCR followed by sanger based sequencing. Journal of Medical Virology. 2016; 88(5): 888–894. pmid:26496186
  24. 24. Kamau E, Tolbert LS, Kortepeter L, Pratt M, Nyakoe N, Muringo L, et al. Development of a highly sensitive genus-specific quantitative reverse transcriptase real-time PCR assay for detection and quantitation of plasmodium by amplifying RNA and DNA of the 18s rRNA genes. Journal of Clinical Microbiology.2011; 49(8):2946–2953. pmid:21653767
  25. 25. Coy MR, Hoffmann M, Kingdom GHN, Kuhns EH, Pelzstelinski KS, Stelinski LL. Nested-quantitative PCR approach with improved sensitivity for the detection of low titer levels of Candidatus liberibacter asiaticus in the Asian citrus Psyllid, Diaphorina citri kuwayama. Journal of Microbiological Methods.2014; 102(7):15–26.
  26. 26. Li W, Hartung JS, Levy L. Quantitative real-time PCR for detection and identification of Candidatus liberibacter species associated with citrus Huanglongbing. J Microbiol Meth. 2006; 66(1):104–115.
  27. 27. Tomimura K, Miyata S, Furuya N, Kubota K, Okuda M, Subandiyah S, et al. Evaluation of genetic diversity among ‘Candidatus Liberibacter asiaticus’ isolates collected in Southeast Asia. Phytopathology. 2009; 99:1062–1069. pmid:19671008
  28. 28. Deng X, Chen J, Feng Z, Shan Z, Guo H, Zhu J, et al. Identification and characterization of the Huanglongbing bacterium in Pummelo from multiple locations in Guangdong, P.R. China. Plant Disease. 2008; 92:513–518.
  29. 29. Bastianel C, Garnier-Semancik M, Renaudin J, Bové JM, Eveillard S. Diversity of ‘Candidatus Liberibacter asiaticus’ based on the OMP gene sequence. Appl Environ Microb.2005; 71:6473–6478.
  30. 30. Ahmad K, Sijam K, Hashim H, Kadir J, Omar SR. Characterization of ‘Candidatus liberibacter asiaticus’ isolated from citrus grandis and citrus reticulata based on 16S rDNA and outer membrane protein (OMP) genes. International Journal of Agriculture aBiology.2009; 11 (4): 401–407.
  31. 31. Lin H, Doddapaneni H, Bai X, Yao J, Zhao X, Civerolo EL. Acquisition of uncharacterized sequences from ‘Candidatus Liberibacter’, an unculturable bacterium, using an improved genomic walking method. Molecular Cellular Probes.2008; 22: 30–37. pmid:17689920
  32. 32. Hong YY, Yi TY, Tan XL, Zhao ZH, Ge F. High ozone (O3) affects the fitness associated with the microbial composition and abundance of Q biotype Bemisia tabaci. Frontiers in Microbiology. 2016; 7:1593. pmid:27799921
  33. 33. Hong YY, Yi TY, Tan XL, Su JW, Ge F. Microbes affected the TYLCCNV transmission rate by the Q biotype whitefly under high O3. Scientific Reports. 2017;| 7: 14412. pmid:29089507
  34. 34. Duan YP, Zhou LJ, Hall DG, Li W, Doddapaneni H, et al. Complete genome sequence of citrus Huanglongbing bacterium, ‘Candidatus Liberibacter asiaticus’ obtained through metagenomics. Molecular Plant Microbe Interactions.2009; 22:1011–1020. pmid:19589076
  35. 35. Lu L, Cheng B, Yao J, Peng A, Du D, Fan G, et al. A new diagnostic system for detection of ‘Candidatus liberibacter asiaticus’ infection in citrus. Plant Disease.2013; 97(10): 1295–1300. pmid:30722132
  36. 36. Ukuda-Hosokawa R, Sadoyama Y, Kishaba M, Kuriwada T, Anbutsu H, Fukatsu T. Infection density dynamics of the citrus greening bacterium "Candidatus liberibacter asiaticus" in field populations of the Psyllid Diaphorina citri and its relevance to the efficiency of pathogen transmission to citrus plants. Appl Environ Microb.2015; 81(11):3728–3736.
  37. 37. Laflèche D, Bové JM. Structures de type mycoplasme dans les feuilles d’orangers atteints de la maladie du greening. Comptes Rendus de l’Académie des Sciences, Paris,1970; 270: 1915–1917.
  38. 38. Hocquellet A, Toorawa P, Bové JM, Garnier M. Detection and identification of the two ‘Candidatus Liberibacter species’ associated with citrus Huanglongbing by PCR amplification of ribosomal protein genes of the Î2 operon. Molecular Cellular Probes.1999; 13:373–379. pmid:10508559
  39. 39. Okuda M, Matsumoto M, Tanaka Y, Subandiyah S, Iwanami T. Characterization of the tufB-secE- nusG-rplKAJL-rpoB gene cluster of the citrus greening organism and detection by loop-mediated isothermal amplification(LAMP). Plant Disease.2005; 89:705–711.
  40. 40. Hu WZ, Wang XF, Zhou Y, Li Z A, Tang K Z, Zhou CY. Diversity of the OMP gene in ‘ Candidatus liberibacter asiaticus’ in China. Journal of Plant Pathologyogy.2011; 93 (1):211–214.
  41. 41. Ángel JE, Hernández EG, Herrera NA, Gómez LY, Castro ÁP, Sepúlveda AM, et al. Citrus Huanglongbing: validation of real-time PCR (qPCR) for the detection of Candidatus liberibacter asiaticus and Candidatus liberibacter americanus in Colombia. Agronomia Colombiana. 2015; 32(3): 377–389.
  42. 42. Manjunath KL, Halbert SE, Ramadugu C, Webb S, Lee RF. Detection of ‘Candidatus Liberibacter asiaticus’ in Diaphorina citri and its importance in the management of citrus Huanglongbing in Florida. Phytopathology. 2008; 98(4):387–396. pmid:18944186
  43. 43. Schneid AD, Rodrigues KL, Chemello D, Tondo EC, Ayub MAZ, Aleixo JAG. Evaluation of an indirect ELISA for the detection of Salmonella in chicken meat. Brazil. Journal of Microbiology. 2006; 37:350–355.
  44. 44. Anderson TP, Beynon KA, Murdoch DR. Comparison of real-time PCR and conventional hemi-nested PCR for the detection of Bordetella pertussis innasopharyngeal samples. Clinic Microbiology and Infection.2003; 9:746–749.
  45. 45. Benyon L, Zhou LJ, Weathersbee A, Duan YP. Nested PCR is essential for the detection of extremely low titer of ‘Candidatus Liberibacter asiaticus’ from citrus and its vector Psyllid Diaphorina citri. Phytopathology. 2008; 98:21–29.
  46. 46. Deng X, Zhou G, Li H, Chen J, Civerolo LE. Nested-PCR detection and sequence confirmation of ‘Candidatus Liberibacter asiaticus’ from Murraya paniculata in Guangdong, China. Disease Notes. 2007; 91: 1051–1058.
  47. 47. Lam WY, Yeung AC, Tang JW, Chan EW, Hui M, Chan PK, et al. Rapid multiplex nested PCR for detection of respiratory viruses. Journal of Clinical Microbiology. 2007; 45:3631–3640. pmid:17804659
  48. 48. Song MK, Chang J, Hong Y, Hong S, Kim SW. Direct multiplex reverse transcription- nested PCR detection of influenza viruses without RNA purification. Journey Microbiology Biotechnology.2009; 19:1470–1474.
  49. 49. Xie ZS, Li J, Shi Q, Xie WL, Yang JR, Chen YF, et al. Damage and epidemics of citrus Huanglongbing in Fujian province. Scientia Agricultura Sinica. 2009; 42(11):3888–3897.
  50. 50. Kunta M, Graca JD, Malik NSA, Louzada ES, Setamou M. Quantitative distribution of Candidatus liberibacter asiaticus in the aerial parts of the Huanglongbing- infected citrus trees in Texas. Hortscience A Publication of the American Society for Horticultural Science. 2014; 49(1): 65–68.