Advertisement

European Journal of Plant Pathology

, Volume 154, Issue 4, pp 863–872 | Cite as

Genetic diversity of ‘Candidatus Liberibacter asiaticus’ in Brazil analyzed in different geographic regions and citrus varieties

  • Larissa Bonevaes de Paula
  • Hong Lin
  • Eduardo Sanches Stuchi
  • Carolina Sardinha Francisco
  • Nágela Gomes Safady
  • Helvécio Della Coletta-FilhoEmail author
Article

Abstract

The bacterium ‘Candidatus Liberibacter asiaticus’ - CLas, the agent associated with citrus huanglongbing disease was first reported in Sao Paulo State in 2004 and has spread throughout the citrus-growing regions of Sao Paulo and further to the states of Minas Gerais and Parana. However, little information is available regarding the genetic diversity of CLas since its introduction. Understanding the genetic diversity of this bacterium is important for tracing migration routes and for identifying evolutionary selection forces that may affect the genetic diversity of this pathogen. Total DNA from 199 HLB-diseased citrus species trees was sampled from geographic regions in Sao Paulo, Parana and Minas Gerais states and the CLas isolates were genotyped by simple sequence DNA repeats (SSR). Nei’s genetic diversity index was observed to be low in all populations (HNei = 0.11–0.26). Wright’s fixation index (FST), which measures population genetic differentiation, did not differ significantly between CLas populations from Sao Paulo State and from Minas Gerais, but significant values (FST = 0.118–0.191) of the Parana CLas population distinguish it from the others. Interestingly, higher values (FST = 0.275–0.445) were observed for the CLas populations obtained from different citrus species compared to sweet orange, suggesting that the citrus genotypes could be driven the genetic diversity of CLas. Clustering analysis supports the FST results that split the CLas samples into three genetically distinct populations. These results indicate that genetically homogeneous populations of CLas infect sweet orange plants in various regions of Sao Paulo State and Minas Gerais, but not Parana, suggesting that different introduction events may have occurred for the Sao Paulo and Parana states.

Keywords

Greening SSR Genetic diversity Citrus pathogen 

Introduction

Citrus huanglongbing (HLB), also known as citrus greening disease, was first reported a century ago in Asia (China and India) (Capoor 1963) and has since spread to more than 40 countries worldwide (Bove 2006). HLB was first reported on the American continent (Sao Paulo State, Brazil) in 2004, and two different species of liberibacteria were associated with the disease: ‘Candidatus Liberibacter asiaticus’, or CLas (Coletta-Filho et al. 2004), and ‘Ca. L. americanus’ (Teixeira et al. 2005). The Asian liberibacterium has spread worldwide and is found everywhere the disease is reported, with the exception of African continent where ‘Ca. L. africanus’ is the predominant HLB-associated bacterium (Haapalainen 2014). The Asian citrus psyllid Diaphorina citri, which has both Citrus spp. and closely related species hosts (Hall et al. 2013), is the main vector for CLas and is responsible for plant-to-plant bacterial transmission. CLas is reported to be transmitted by the psyllid in a persistent, propagative manner (Canale et al. 2017), with increasing titers over time in the insect vector (Ammar et al. 2011) and also in the plants (Coletta-Filho et al. 2009).

Already at five years after the first identification of liberibacteria infected citrus trees in Brazil, the Asian species of the bacterium was prevalent in HLB-diseased citrus trees in all geographic regions of the Brazilian states Sao Paulo, Minas Gerais, and Parana (Gottwald 2010). However, little information is known about the effective population size of CLas present in HLB-infected citrus-trees in these regions. Understanding the population genetic diversity of CLas is useful for monitoring the micro-evolutionary process of the pathogen over short time scales (changes in the allelic frequency and genotypes) to trace gene flow and, consequently, migratory routes as well as to provide information for researches aiming CLas resistance.

As CLas is not yet cultivable, PCR-based technique is one of the most accessible strategies for typing this bacterium. The conserved 16S-rRNA gene is commonly used for genetic diversity studies in bacteria (Weisburg et al. 1991), which has been used to both detect and genotype CLas (Subandiyah et al. 2000; Tomimura et al. 2009). However, due to its limited sequence variability, this gene does not provide sufficient genetic information for intra-species diversity studies. With the availability of full genomic sequence of CLas (Katoh et al. 2014; Duan et al. 2009) it is now possible to design primers that target specific regions of the CLas genome, leading to improve estimations of intra-species genetic variability. Significant sequence variations were inferred among global isolates of CLas by targeting hyper-variable genomic regions based on phage sequences (Zhou et al. 2013) and 4 prophage types were defined (Type A to Type D). Hypervariable sequences based on simple sequence repeat (SSR) regions have also been successfully used for typing CLas (Chen et al. 2010; Katoh et al. 2011; Zhou et al. 2011; Islam et al. 2012). A panel of seven polymorphic SSR primers was used (Islam et al. 2012) for a worldwide genetic diversity study of CLas that included Brazil. However, this study covered only 22 isolates sampled from a restricted geographic region of Sao Paulo State and from only one citrus genotype. Furthermore, HLB has now spread throughout the states of Sao Paulo, Parana, and Minas Gerais (Gottwald 2010), so a broad sampling strategy is required to determine the genetic diversity of CLas.

Here, the genetic diversity of CLas that represents the most important citrus-growing regions of the states of Sao Paulo, Parana and Minas Gerais was sampled and analyzed at the population level. In addition to the geographic structure level, samples from different CLas-infected citrus genotypes were analyzed.

Material and methods

Sample origins

A total of 199 citrus samples infected by CLas were sampled from private orchards with the permission of the respective owners. Among these samples, 154 were collected from sweet orange (Citrus sinensis L. Osbeck) varieties grown in different geographic regions of Sao Paulo State (n = 128), Parana (n = 11), and Minas Gerais (n = 15). Another 45 samples came from different citrus species (Citrus spp.), including C. sinensis genotypes, sampled from the citrus germplasm bank of Centro de Citricultura Sylvio Moreira, IAC, in the east region of Sao Paulo State (Table 1). This germplasm collection was established at least 20 years before the first report of HLB in Sao Paulo state (Coletta-Filho et al. 2004; Teixeira et al. 2005), thus, we assume that all HLB-diseased trees from the collection were naturally infected.
Table 1

Origin of samples used for the analysis

Sample origin

Municipalities

Number of samples

Geographic region

 Sao Paulo State

 

  North

Bebedouro, Catanduva, Colômbia, Jaboticabal, Nova Granada

27

  East

Araras, Arthur Nogueira, Casa Branca, Conchal, Corderópolis, Jaguariuna, Jarinú, Limeira, Mogi Guaçu, Mogi Mirim, Piracicaba, Pirassununga, Santo Antonio de Posse

56

  Center

Araraquara, Brotas, Bariri, Santa Maria da Serra, Tabatinga

21

  South

Avaré, Cabreúva, Pratânia, Itapeva, Pardinho, Pratânia

24

 Minas Gerais State

Carmo do Rio Claro, Guaxupé

15

 Paraná State

Paranavaí

11

Citrus speciesa   

Rough lemon – C. limonia (7); Citrumelo F80–7 – P. trifoliata x C. paradise (1); Citrange C35 - P. trifoliata x C. sinensis (2); Citron – C. medica (1); Kharna citrus- C. kharna (1) Sour orange – C. aurantium (2); Lemon - C. limon (4); Acid lime – C. aurantifolia (2); Volkameriano lemon – C. volkameriana (1); Mandarin – C. reticulata (3); Grapefruit – C. grandis (2); Tangors - C. reticulata x C. sinensis (1); sweet orange varieties - C. sinensis (8); Tangelo - C. reticulata x C. paradise (1); unknown samples (9)

aSamples collected at Germplasm Bank in Cordeirópolis (eastern São Paulo State), totalizing 45 genotypes 

DNA extraction

Total DNA was obtained from the petioles and main ribs of HLB-symptomatic leaves by crushing the material using TissueLyser equipment (QIAGEN, Valencia, CA) that was operated at 30 Hz for 2 min, followed by extraction using the CTAB protocol (Murray and Thompson 1980). The presence of CLas was confirmed by qPCR using primers and probe based on elongation factor Ts CLas gene developed by Lin et al. (2010), adopting the same conditions used by the authors in the reaction and cycling. All amplifications were performed in duplicate, using the ABI 7500 Fast thermal cycler (Life Technology Corporation, Carlsbad, CA) with the probe label with FAM/Iowa Black FQ (IDT Inc., Coralville, IA).

Amplification of SSR loci

Eight SSR loci previously described (Katoh et al. 2011; Islam et al. 2012) and a new one developed for this study were used for genotyping strains (Table 2). The new SSR loci (CC01) was identify on the genome of Psy62 strain of CLas (Duan et al. 2009) with the software Tandem Repeat Finder version 2.02 (Benson 1999). Primers flanking this novel repeat region were designed with Primer3 version 0.4.0 (Untergrasser et al. 2012). All amplifications were performed in a final volume of 13.0 μL containing the following: 25–50 ng of DNA, 6.50 μL of 2xTaq PCR Master Mix (QIAGEN, Valencia, CA) and 3 pmol of each primer (Table 2). The following program was used for PCR amplification: a denaturation step at 94 °C for 2 min, followed by 30 cycles of 40 s at 94 °C, 40 s at 58 °C or at 60 °C (only for primer set SSR-B), and 40 s at 72 °C, followed by a 5 min extension at 72 °C. Successfully amplified products were determined by assessing 3 μL of the PCR products by 2% agarose gel electrophoresis with TAE buffer.
Table 2

General information about the primers and multi-locus capillary electrophoresis used for typing ‘Ca. L. asiaticus’ populations

Seta

Locus

Dyeb

Fragment size range (bp)c

Number of alleles

Sequence of motif

Reference

1

SSR-A

FAM

287–363

9

(TATTCTG)8

Islam et al. 2012

SSR-B

VIC

203 and 242

2

(TTTAA)6

Islam et al. 2012

SSR-E

NED

227-281

11

(CTTGTGT)5

Islam et al. 2012

Total

 

22

  

2

SSR-C

VIC

239

1

(CAGT)8

Islam et al. 2012

SSR-D

NED

176

1

(TTC)5

Islam et al. 2012

SSR-F

FAM

203 and 238

2

(TTTACATC)3

Islam et al. 2012

Total

  

4

  

3

K005

NED

629–677

6

(AGACACA)5

Katoh et al. 2011

K077

VIC

512

1

(TTTG)14

Katoh et al. 2011

CC01d

PET

187

1

(TTAAT)5

This study

Total

  

8

  
 

Overall

  

34

  

aSet of amplicons used in multi-locus capillary electrophoresis, also called multi-locus electrophoresis analysis, MLEa

bFor each respective locus, the fluorescence dyes 6FAM (blue), NED (yellow), PET (red), and VIC (green) were used for labeling the forward primers

cRange of fragment sizes, measured in base pairs (bp)

dSequences of Forward (CCCTTTACTGATATGTTTCCGCATA) and Reverse (CGGAAGTGATAATAACTACAGCAATAAG) primers

Fragment analysis of SSR products

Prior to capillary electrophoresis, 2 μL of each SSR amplified loci was mixed with 38 μL of autoclaved Milli-Q water. Three μL of each diluted SSR-loci was multiplexed according to different multi-locus electrophoresis analysis (MLEa) sets as presented in Table 2. One microliter of the mixed amplifications was added to 10 μL of Hi-Di Formamide with 0.1 μL of the GeneScan™ 500-LIZ Size Standard (both from Applied Biosystems, Foster City, CA). After DNA denaturation for 5 min at 95 °C followed by cooling on ice for 2 min, samples were submitted to capillary electrophoresis in an ABI 3730xl DNA sequencer (Applied Biosystems) with the LIZ500–3730 standard setting on the GeneScan module with filter set G5. The GeneScan data were analyzed with Peak Scanner V1.0 software (Applied Biosystems).

Sequencing of amplicons

Amplicons generated with SSR primer pairs were randomly chosen and directly sequenced in an ABI 3730xl DNA sequencer to double-check the presence of the motifs predicted by the Peak Scanner software. To set up FAST sequences from the reads, we used the CLC Genomic Workbench platform (QIAGEN).

Statistical analyses

Several statistical parameters were measured to infer the genotypic and genetic diversity as well as the population genetic structure of CLas.

Genotypic and genetic analysis

Multi-locus microsatellite genotype (MLMG) analysis for each sample was carried out by using GenoDive software (Meirmans and van Tienderen 2004), and samples with the same MLMG were treated as clones. Simpson’s diversity index (D) was estimated as D = 1-∑P2r (r = 1 to s), where Pr is the relative abundance of the rth genotype in the population (1 represents infinite diversity, and 0 represents no diversity) (He and Hu 2005). The mean genetic diversity (HNei), corrected for the number of individuals (n) in a population [(1 - ∑pi2) x (n/n-1)], where pi is the frequency of allele i at the locus], was estimated using FSTAT software, version 2.9.3.2 (Goudet 1995). A bootstrapping test using 1000 randomizations was performed between pairs of populations to assess differences in clonal diversity.

Differentiation among populations

The null hypothesis of non-differentiation among pair-wise populations was tested by using the FST index (Wright 1951) in GenoDive software. Populations were considered significantly differentiated (P < 0.05) when the observed value of FST was larger than 95% of the value obtained with 1000 bootstraps of MLMG over the populations. The number of genetically homogeneous clusters within each predefined population was estimated with BAPS v.5.2 (Corander et al. 2003) by performing independent runs using the “clustering of individuals” as recommended previously (Waples and Gaggiotti 2006), with the subpopulation number (K) ranging from 1 to 20. Once we identified the best value for K, we reanalyzed the data with BAPS using the “Fixed-K module”, which was run 1000 times to identify individuals that composed each genetic cluster. We also performed principal coordinate analysis (PCoA) to plot major patterns within a multivariate dataset (e.g., multiple loci and multiple samples) by using GeneAlex version 6.5 (Peakall and Smouse 2012).

Results

Genetic diversity of CLas in HLB diseased citrus plants

From four polymorphic SSR loci described by Katoh et al. (2011) plus seven other loci describe by Islam et al. (2012) we selected eight sets based on PCR products with only one peak as reveled by capillary electrophoresis. In addition, a new set of primer (CC01) was designed totalizing nine sets used in this study. Off this total, four loci (SSR-C, SSR-D, K077, and CC01) were monomorphic for all 199 samples analyzed (S1 Table). On the other hand, the loci SSR-E, SSR-A, and K005 showed 11, 9, and 6 alleles, respectively. Only two alleles among all samples were produced by the loci SSR-B and SSR-F; 64.7% of the different alleles (n = 34) observed for the analyzed CLas populations were generated by the set of loci used for multi-locus electrophoresis analysis - MLEa (Table 2). The combination of these different alleles resulted in 85 multi-locus microsatellite genotypes (MLMGs) from 199 analyzed samples (Table 3). A higher number of MLMGs was observed for the CLas population from Paraná (10 of 11 analyzed samples), which resulted in a higher value for Simpson’s diversity index (D = 0.98). However, no significant difference was observed for the D value among other CLas populations except for the population from Southern Sao Paulo State (D = 0.66). Interestingly, the D value (0.82) for samples of CLas from Citrus spp. populations was not higher than those for other CLas populations sampled from homogeneous hosts, such as commercial sweet orange varieties (Table 3). The allelic frequency was uniform across all populations, resulting in HNei values that were not significantly different and that ranged from 0.22 to 0.25 (Table 3).
Table 3

Genotypic and genetic diversity of ‘Candidatus L. asiaticus’ samples from HLB diseased citrus trees in Brazil

aCLas population

Number of strains

Number of bMLMGs

Simpson’s diversity index (D)c

Genetic diversity HNei

North SPS

27

15

0.84 a

0.25 a

East SPS

56

21

0.91 a

0.25 a

Center SPS

21

11

0.91 a

0.25 a

South SPS

24

8

0.66 b

0.23 a

Minas Gerais State

15

9

0.92 a

0.23 a

Paraná State

11

10

0.98 a

0.24 a

Citrus spp.

45

11

0.82 a

0.22 a

Overall

199

85

  

aSee Materials and methods for details of ‘Candidatus L. asiaticus’ populations

bMLMG – Multi-locus microsatellite genotype

cMeans followed by the same letter were significantly different (P ≤ 0.05) based on 1000 pairwise bootstrap tests

Validation of SSR markers by resequencing amplicons

To double-check the number of motifs present in SSR amplicons as predicted by the peak scanner, some amplicons were sequenced. For the two randomly chosen samples from the East population, a typical plus one/minus one variation was observed in the number of repeats for the motifs SSR-A (+1), SSR-E (+3), and K005 (+3), which corresponded to the estimated variation of the fragment size (Table 4).
Table 4

Number of repeats of motifs (in brackets) present in three loci in samples of ‘Candidatus Liberibacter asiaticus’ from the East São Paulo State population and its relationship with the amplicon size (base pairs) predicted by fragment analysis software

Ca. L. asiaticus’ samples

Locia

SSR-A

SSR-E

K005

IndE28

339 (17)

271 (13)

674(16)

IndE29

331 (16)

251 (10)

653 (13)

aFor the motifs present at each locus, see Table 2

Genetic structure among CLas populations sampled at different geographic regions

The hypothesis that populations of CLas sampled from different geographic regions were structured according to their respective origin was tested by using 3 strategies. First, the population differentiation due to the genetic structure was measured using Wright’s FST and the stepwise mutation model (SMM). Weak (FST from 0.00 to 0.033) and non-significant (P ≤ 0.05) fixation index values were found for all of the pairwise comparisons of CLas populations sampled from HLB-diseased plants in various regions of Sao Paulo State (North, East, Center, and South) and in Minas Gerais State, indicating that there was no genetic differentiation between those populations (Table 5). A moderate and statistically significant value for FST (from 0.99 to 0.135) was observed in HLB-diseased plants from Parana State compared to other CLas populations (Table 5). Moreover, larger and significant values for FST, ranging from 0.290 to 0.445 (Table 5), were obtained for CLas populations collected from other citrus species. The influence of citrus species hosting genetically different CLas populations was shown by the significant fixation index (FST = 0.298) between CLas populations obtained from diverse citrus species and from sweet orange alone, both of which were sampled from the eastern region of Sao Paulo State. Bayesian analyses were run in BAPS software using the clustering of individuals and mixture modules and showed results similar to those obtained with the F statistic. Essentially, all of the CLas samples from HLB-diseased trees from the northern, eastern, central, and southern regions of Sao Paulo State, as well as those from Minas Gerais State, were in the same cluster. Samples from Paraná State and Citrus spp. were segregated into two other clusters (Fig. 1). Finally, principal coordinates analysis (PcoA) clearly segregated the CLas populations into three well split clusters (Fig. 2), supporting the results obtained by both F statistic and clustering by Bayesian analysis. Additionally, PCoA placed the CLas population from Citrus spp. distant from the other two CLas populations, reinforcing the higher values obtained for the FST index in that population.
Table 5

Measure of the pairwise population differentiation based on the FST value (below diagonal) and its statistical significance (above diagonal)

CLas populations

North SPa

East SP

Center SP

South SP

Minas Gerais

Parana

Citrus spp.

North SP

 

b0.659

0.782

0.763

0.414

0.019

0.001

East SP

0.014

 

0.545

0.515

0.218

0.033

0.001

Center SP

0.033

0.009

 

0.446

0.734

0.017

0.001

South SP

0.014

0.005

0.009

 

0.614

0.007

0.001

Minas Gerais

0.017

0.031

0.000

0.083

 

0.023

0.007

Parana

0.099

0.074

0.098

0.109

0.135

  

Citrus spp.

0.302

0.290

0.368

0.298

0.445

0.388

0.001

aSP – Sao Paulo State

bSignificant (P ≤ 0.05, after Bonferroni correction) values based on 1000 randomizations

Fig. 1

Bayesian inferences on the structure of ‘Ca. Liberibacter asiaticus’ populations sampled from HLB-diseased trees in Brazil as estimated by BAPS software using the option “clustering of individuals” and mixture. The same colors represent genetically homogeneous populations. Center, North, East and South – geographic regions of São Paulo State; MG – Minas Gerais State; PR – Paraná State; Citrus spp. – different citrus species grown in South São Paulo State

Fig. 2

Principal coordinate analysis (PCoA) of CLas populations sampled from different regions and citrus species in Brazil. PR – Paraná State; MG – Minas Gerais State; Center, North, East and South – geographic regions of São Paulo State; Citrus spp. – different citrus species grown in South São Paulo State

Discussion

Prior to publication of the complete genomic sequence of CLas (Duan et al. 2009), the genetic information for this species was based only on 16S rDNA, 16–23 intergenic region sequences (ITS), and genes for outer membrane proteins genes (Subandiyah et al. 2000; Bastianel et al. 2005; Ding et al. 2009). Those conserved genomic regions provided limited genetic information for studies of intraspecies diversity, with a few different strains characterized worldwide, including from Asia, which is where this disease originated (Ding et al. 2009). Recently, molecular markers targeting rapidly evolving genomic regions, such as simple sequence repeats (SSRs), have been incorporated into CLas genetic diversity studies (Chen et al. 2010; Katoh et al. 2011; Zhou et al. 2011; Islam et al. 2012). In addition to the high resolution at the strain level, due to the high polymorphism of these markers (Katoh et al. 2011), this strategy resulted in stable profiles upon passage of CLas through different hosts (insect vector and plant) over a period of 5 years (Matos et al. 2013). Sequencing of three loci confirmed the ‘gain’ and ‘loss’ of the repeat motifs as well as a direct effect on amplicon size (Table 4), reinforcing the validation of the variable repeats as a repeatability typing methodology (Lista et al. 2006).

CLas was probably introduced to Brazil from East-Southeast Asia (Islam et al. 2012). Despite the brief presence of this bacterium in Brazil (around 10 years), approximately 55% (five out of nine) of the SSR loci were polymorphic, but this resulted in few alleles per locus and moderate values of Nei’s genetic diversity index (Tables 2 and 3). An early study focusing on CLas populations from Sao Paulo State found 63% of the MLMGs among 22 analyzed samples, with an average of 2.7 alleles per locus and a genetic diversity index value of 0.313 (Islam et al. 2012). Although the two studies were conducted using different numbers of samples from distinct places, the similar values suggest a uniform distribution of genetic variants of CLas throughout HLB infected orchards. On the other hand, the values of Nei’s genetic diversity index from CLas populations in the present study were significantly lower than those observed for populations from Japan (HNei = 0.60 to 0.82) (Katoh et al. 2011), which could be explained by a gap of hundreds of years between the Japanese and Brazilian CLas populations in the field. However, contemporaneous populations of CLas from South, North and Central America showed similar genetic diversity index values (Islam et al. 2012; Matos et al. 2013) .

The weak and statistically indistinguishable values of Wright’s fixation index (FST) confirm the uniform distribution of the genetic variants of CLas in the different geographic regions (northern, southern, eastern, and central) in Sao Paulo State (Table 5). Likewise, the FST values were not distinct from samples taken from nearby orchards in Minas Gerais State, which suggests a single genetically homogeneous population. Although using only two CLas genomic loci Deng et al. (2014) also mentioned the presence of homogenous CLas population in Sao Paulo State by analyzing 85 isolates from 18 municipalities which reinforced the hypothesis of a single introduction in Sao Paulo State. These finding is consistent with the hypothesis that sufficient allele homogenization is occurring among the subpopulations by migration and gene flow (Slatkin 1987). The insect vector of the CLas, the Asian citrus psyllid Diaphorina citri, is an extremely mobile insect with the potential to fly up to 1.5 km or even longer distances when carried by wind (Halbert and Manjunath 2004; Kobori et al. 2011). This insect is able to reproduce and feed on all citrus species as well as on closely related species, including Murraya spp. (Halbert and Manjunath 2004). Their movement from plant to plant is known to be influenced by the availability of food, the physiological stage of the host, and oviposition sites (Tomaseto et al. 2016). Bearing in mind that species of Citrus and Murraya are widespread throughout Sao Paulo State as well as in the bordering municipalities of Southern Minas Gerais State (specifically, Carmo do Rio Claro and Guaxupé), the availability of susceptible hosts could explain the absence of genetic differences between CLas subpopulations across Sao Paulo State. We hypothesized that Asian citrus psyllid adults may be primarily responsible for the absence of genetic differences by mixing different CLas genotypes across orchards and regions during the feeding process. In addition to the fairly recent presence of CLas in Sao Paulo State, the homogeneity of the environment and narrow genetic base of susceptible sampled hosts (only four commercial sweet orange varieties) may constitute selectively neutral conditions with a low potential to modulate the CLas population size. Different from the genetic homogeneity observed among CLas populations as cited above, the CLas population from Paranavaí (Parana State) was genetically different compared to populations from other regions. Local environmental conditions may contribute to the establishment of more adapted microorganisms (Restrepo et al. 2004). However, the possibility of a new CLas introduction from a different population could not be discarded. New samplings from different citrus regions of Parana State, including from near Paranavaí, must be performed to test this hypothesis. Another genetically distinct CLas population was observed colonizing the citrus spp. population (Table 5), but no specific CLas haplotype was associated with any citrus species, similar to findings obtained by Tomimura et al. (2009). Currently, there is no information regarding the relationship between the heterogeneous host population (different citrus genotypes) and CLas diversity. However, previous research have shown that some citrus species, mainly Poncirus trifoliata and hybrids, are more tolerant of CLas infection and colonization (Albrecht and Bowman 2011; Ramadugu et al. 2016; Borgoni et al. 2014) and moreover are less attractive to Asian citrus psyllids (Ma and Amos 2012). These host characteristics can potentially exert a bottleneck effect on prevalence of specific MLMG of ‘Ca. Liberibacter asiaticus’. In fact, the genetic diversity index (HNei) values for CLas populations from different citrus species were not significantly different from those of other CLas populations sampled from sweet orange (Table 3).

The results from Bayesian clustering analysis (Fig. 1) and principal coordinate analysis (PCoA) (Fig. 2) clustered the 85 CLas haplotypes into three clusters and are consistent with the results for Wright’s fixation index (FST). The clusters correspond to three genetically distinct populations: 1. Different geographic regions of Sao Paulo State and Minas Gerais; 2. Paraná; and 3. Citrus spp. (different citrus species). This low-variability and homogeneous distribution of CLas haplotypes among the geographic regions is advantageous for processes aimed at resistance against CLas based on knowledge that pathogen populations with limited variation are less likely to overcome host resistance. On the other hand, citrus species influenced the genetic structure of CLas populations, emphasizing the importance of biotic interactions in driving pathogen evolution (Brockhurst et al. 2014).

In conclusion, approximately 10 years after the first report of CLas in Brazil, the HLB agent has been found in all of the citrus-growing regions in Sao Paulo State (approximately 400 million ha) as well as in Parana and Minas Gerais States. Overall, low genetic diversity was observed for all of the CLas strains sampled. CLas from HLB-diseased sweet orange plants showed weak genetic structure, with the pathogen splitting into three populations: one composed of strains from all the citrus-growing regions in Sao Paulo State and Minas Gerais; the other of strains sampled in Parana State, and the third of strains sampled from different citrus species. The brief presence of CLas in Brazil, from apparently only one introduction, may explain the low genetic diversity observed for this pathogen.

Notes

Acknowledgments

We thank our lab colleagues for constructive suggestions and discussions, and we also thank the growers who granted us access to their farms to collect the samples. The authors, L.B. de Paula thanks CAPES (Coordination for the Improvement of Higher Level Personnel) for Master’s degree scholarship and H. D. Coletta-Filho acknowledges CNPq for research fellowship (Proc. No. 313676/2017-8).

Funding

This work was funded by Brazilian National Council for Scientific and Technological Development (CNPq - project number 481667/2012–1).

Compliance with ethical standards

Conflict of interests

All the authors have no conflict of interests.

Supplementary material

10658_2019_1695_MOESM1_ESM.xlsx (15 kb)
ESM 1 (XLSX 14 kb)

References

  1. Albrecht, U., & Bowman, K. D. (2011). Tolerance of the trifoliate citrus hybrid US-897 (Citrus reticulata Blanco × Poncirus trifoliata L. Raf.) to huanglongbing. HortScience, 46, 16–22.CrossRefGoogle Scholar
  2. Ammar, E., Shatters, R. G., Lynch, C., & Hall, D. G. (2011). Detection and relative titer of “Candidatus Liberibacter asiaticus” in the salivary glands and alimentary canal of Diaphorina citri (Hemiptera: Psyllidae) vector of citrus huanglongbing disease. Annals of the Entomological Society of America, 104, 526–533.CrossRefGoogle Scholar
  3. Bastianel, C., Renaudin, J., Bove, J. M., & Eveillard, S. (2005). Diversity of ‘Candidatus Liberibacter asiaticus’ based on the omp gene sequence. Applied and Environmental Microbiology, 71, 6473–6478.CrossRefPubMedPubMedCentralGoogle Scholar
  4. Benson, G. (1999). Tandem repeats finder: a program to analyze DNA sequences. Oxford University Press Nucleic Acids Research, 27, 573–580.CrossRefGoogle Scholar
  5. Borgoni, P. C., Vendramim, J. D., Lourencão, A. L., & Machado, M. A. (2014). Resistance of citrus and related genera to Diaphorina citri Kuwayama (Hemiptera: Liviidae). Neotropical Entomology, 43, 465–469.CrossRefPubMedGoogle Scholar
  6. Bove, J. M. (2006). Huanglongbing: a destructive, newly-emerging, century-old disease of citrus. Journal of Plant Pathology, 88, 7–37.Google Scholar
  7. Brockhurst, M. A., Chapman, T., King, K. C., Mank, J. E., Paterson, S., & Hurst, G. D. D. (2014). Running with the Red Queen: the role of biotic conflicts in evolution. Proceedings of the Royal Society B, 281, 20141382.CrossRefPubMedGoogle Scholar
  8. Canale, M. C., Tomaseto, A. F., Haddad, M. d. L., Coletta-Filho, H. D., & Lopes, J. S. (2017). Latency and persistence of ‘Candidatus Liberibacter asiaticus’ in its psyllid vector, Diaphorina citri Kuwayama (Hemiptera: Liviidae). Phytopathology, 107, 264–272.CrossRefPubMedGoogle Scholar
  9. Capoor, S. P. (1963). Decline of citrus trees in India. Bulletin, National Institute of Science India, 234, 48–64.Google Scholar
  10. Chen, J., Deng, X., Sun, X., Jones, D., Irey, M., & Civerolo, E. (2010). Guangdong and Florida populations of ‘Candidatus Liberibacter asiaticus’ distinguished by a genomic locus with short tandem repeats. Phytopathology, 100, 567–572.CrossRefPubMedGoogle Scholar
  11. Coletta-Filho, H. D., Targon, M. L. P. N., Takita, M. A., De Negri, J. D., Pompeu, J., Jr., & Machado, M. A. (2004). First report of the causal agent of Huanglongbing (‘Candidatus Liberibacter asiaticus’) in Brazil. Plant Disease, 88, 1382.CrossRefPubMedGoogle Scholar
  12. Coletta-Filho, H. D., Carlos, E. F., Alves, K. C. S., Pereira, M. A. R., Boscariol-Camargo, R. L., de Souza, A. A., & Machado, M. A. (2009). In planta multiplication and graft transmission of ‘Candidatus Liberibacter asiaticus’ revealed by real-time PCR. European Journal of Plant Pathology, 1126, 53–60.Google Scholar
  13. Corander, J., Waldmann, P., & Sillampaa, M. J. (2003). Bayesian analysis of genetic differentiation between populations. Genetics, 163, 367–374.PubMedPubMedCentralGoogle Scholar
  14. Deng, X., Lopes, S., Wang, X., Sun, X., Jones, D., Irey, M., Civerolo, E., & Chen, J. (2014). Characterization of ‘Candidatus Liberibacter asiaticus’ populations by double-locus analyses. Current Microbiology, 69, 554–560.CrossRefPubMedGoogle Scholar
  15. Ding, F., Deng, X., Hong, N., Zhong, Y., Wang, G., & Yi, G. (2009). Phylogenetic analysis of the citrus Huanglongbing (HLB) bacterium based on the sequences of 16S rDNA and 16S/23S rDNA intergenic regions among isolates in China. European Journal of Plant Pathology, 124, 495–503.CrossRefGoogle Scholar
  16. Duan, Y., Zhou, L., Hall, D. G., Li, W., Doddapaneni, H., Lin, H., Liu, L., Vahling, C. M., Gabriel, D. W., Williams, K. P., Dickerman, A., Sun, Y., & Gottwald, T. (2009). Complete genome sequence of citrus huanglongbing bacterium, ‘Candidatus Liberibacter asiaticus’ obtained through metagenomics. Molecular Plant-Microbe Interactions, 22, 1011–1020.CrossRefPubMedGoogle Scholar
  17. Gottwald, T. R. (2010). Current epidemiological understanding of citrus huanglongbing. Annual Review of Phytopathology, 48, 119–139.CrossRefPubMedGoogle Scholar
  18. Goudet, J. (1995). FSTAT (version 1.2): a computer program to calculated F-statistics. Journal of Heredity, 86, 485–486.CrossRefGoogle Scholar
  19. Haapalainen, M. (2014). Biology and epidemics of Candidatus Liberibacter species, psyllid-transmitted plant-pathogenic bacteria. Annals of Applied Biology, 165, 172–198.CrossRefGoogle Scholar
  20. Halbert, S. E., & Manjunath, K. L. (2004). Asian Citrus Psyllids (Sternorrhyncha: Psyllidae) and greening disease of citrus: a literature review and assessment of risk in Florida. Florida Entomologist, 87, 330–353.CrossRefGoogle Scholar
  21. Hall, D. G., Richardson, M. L., Ammar, E. D., & Halbert, S. E. (2013). Asian citrus psyllid, Diaphorina citri, vector of citrus huanglongbing disease. Entomologia Experimentalis et Applicata, 146, 207–223.CrossRefGoogle Scholar
  22. He, F., & Hu, X. S. (2005). Hubbell’s fundamental biodiversity parameter and the Simpson diversity index. Ecology Letters, 8, 386–390.CrossRefGoogle Scholar
  23. Islam, M. S., Glynn, J. M., Bai, Y., Duan, Y.-P., Coletta-Filho, H. D., Kuruba, G., Civerolo, E. L., & Lin, H. (2012). Multilocus microsatellite analysis of ‘Candidatus Liberibacter asiaticus’ associated with citrus Huanglongbing worldwide. BMC Microbiology, 12, 39.CrossRefPubMedPubMedCentralGoogle Scholar
  24. Katoh, H., Subandiyah, S., Tomimura, K., Okuda, M., Su, H. J., & Iwanami, T. (2011). Differentiation of ‘Candidatus Liberibacter asiaticus’ isolates by variable-number tandem-repeat analysis. Applied and Environmental Microbiology, 77, 1910–1917.CrossRefPubMedPubMedCentralGoogle Scholar
  25. Katoh, H., Miyata, S. I., Inoue, H., & Iwanami, T. (2014). Unique features of a Japanese ‘Candidatus Liberibacter asiaticus’ strain revealed by whole genome sequencing. PLoS One, 9(9), e106109.CrossRefPubMedPubMedCentralGoogle Scholar
  26. Kobori, Y., Nakata, T., Ohto, Y., & Takasu, F. (2011). Dispersal of adult Asian citrus psyllid, Diaphorina citri Kuwayama (Homoptera: Psyllidae), the vector of citrus greening disease, in artificial release experiments. Applied Entomology and Zoology, 46, 27–30.CrossRefGoogle Scholar
  27. Lin, H., Chen, C., Doddapaneni, H., Duan, Y., Civerolo, E. L., Bai, X., & Zhao, X. (2010). A new diagnostic system for ultra-sensitive and specific detection and quantification of ‘Candidatus Liberibacter asiaticus’, the bacterium associated with citrus huanglongbing. Journal of Microbiology Methods, 81, 17–25.CrossRefGoogle Scholar
  28. Lista, F., Faggioni, G., Valjevac, S., Ciammaruconi, A., Vaissaire, J., le Doujet, C., Gorgé, O., de Santis, R., Carattoli, A., Ciervo, A., Fasanella, A., Orsini, F., D'Amelio, R., Pourcel, C., Cassone, A., & Vergnaud, G. (2006). Genotyping of Bacillus anthracis strains based on automated capillary 25-loci multiple locus variable-number tandem repeats analysis. BMC Microbiology, 6, 33.CrossRefPubMedPubMedCentralGoogle Scholar
  29. Ma, J., & Amos, C. I. (2012). Principal components analysis of population admixture. PLoS One, 7(7).Google Scholar
  30. Matos, L. A., Hilf, M. E., Chen, J., & Folimonova, S. Y. (2013). Validation of “variable number of tandem repeat”-based approach for examination of ‘Candidatus Liberibacter asiaticus’ diversity and its applications for the analysis of the pathogen populations in the areas of recent introduction. PlosOne, 8(11).Google Scholar
  31. Meirmans, P. G., & van Tienderen, P. H. (2004). GENOTYPE and GENODIVE: two programs for the analysis of genetic diversity of asexual organisms. Molecular Ecology Notes Resources, 4, 792–794.CrossRefGoogle Scholar
  32. Murray, M. G., & Thompson, W. F. (1980). Rapid isolation of high molecular weight plant DNA. Nucleic Acids Research, 8, 4321–4325.CrossRefPubMedPubMedCentralGoogle Scholar
  33. Peakall, R., & Smouse, P. E. (2012). GenALEx 6.5: Genetic analysis in Excel. Population genetic software for teaching and research-an update. Bioinformatics, 28, 2537–2539.CrossRefPubMedPubMedCentralGoogle Scholar
  34. Ramadugu, C., Keremane, M. L., Halbert, S. E., Duan, Y.-P., Roose, M. L., Stover, E., & Lee, R. F. (2016). Long-term field evaluation reveals huanglongbing resistance in Citrus relatives. Plant Disease, 100, 1858–1869.CrossRefPubMedGoogle Scholar
  35. Restrepo, S., Velez, C. M., & Duque, M. C. (2004). Genetic structure and population dynamics of Xanthomonas axonopodis pv. manihotis in Colombia from 1995 to 1999. Applied and Environmental Microbiology, 70, 255–261.CrossRefPubMedPubMedCentralGoogle Scholar
  36. Slatkin, M. (1987). Gene flow and geographic structure of natural populations. Science, 236, 787–792.CrossRefPubMedGoogle Scholar
  37. Subandiyah, S., Iwanami, T., Tsuyumu, S., & Ieki, H. (2000). Comparison of 16S rDNA and 16S/23S intergenic region sequences among citrus greening organisms in Asia. Plant Disease, 84, 15–18.CrossRefPubMedGoogle Scholar
  38. Teixeira, C. D., Saillard, C., Eveillard, S., Danet, J. L., da Costa, P. I., Ayres, A. J., & Bové, J. (2005). ‘Candidatus Liberibacter americanus’, associated with citrus huanglongbing (greening disease) in São Paulo State, Brazil. International Journal of Systematic and Evolutionary Microbiology, 55, 1857–1862.CrossRefGoogle Scholar
  39. Tomaseto, A. F., Krugner, R., & Lopes, J. R. S. (2016). Effect of plant barriers and citrus leaf age on dispersal of Diaphorina citri (Hemiptera: Liviidae). Journal of Applied Entomology, 140, 91–102.CrossRefGoogle Scholar
  40. Tomimura, K., Miyata, S.-I., Furuya, N., Kubota, K., Okuda, M., Subandiyah, S., Hung, T. H., Su, H. J., & Iwanami, T. (2009). Evaluation of genetic diversity among “Candidatus Liberibacter asiaticus” isolates collected in Southeast Asia. Phytopathology, 99, 1062–1069.CrossRefPubMedGoogle Scholar
  41. Untergrasser, A., Cutcutache, I., Koressaar, T., Ye, J., Faircloth, B. C., Remm, M., & Rozen, S. G. (2012). Primer3 new capabilities and interfaces. Nucleic Acids Research, 40, 115.CrossRefGoogle Scholar
  42. Waples, R. S., & Gaggiotti, O. (2006). What is a population? An empirical evaluation of some genetic methods for identifying the number of gene pools and their degree of connectivity. Molecular Ecology, 15, 1419–1439.CrossRefPubMedGoogle Scholar
  43. Weisburg, W. G., Barns, S. M., Pelletier, D. A., & Lane, D. J. (1991). 16S ribosomal DNA amplification for phylogenetic study. Journal of Bacteriology, 173, 697–703.CrossRefPubMedPubMedCentralGoogle Scholar
  44. Wright, S. (1951). The genetical structure of populations. Annals of Eugenics, 15, 322–354.Google Scholar
  45. Zhou, L., Powell, C. A., Hoffman, M. T., Li, W., Fan, G., Liu, B., Lin, H., & Duan, Y.-P. (2011). Diversity and plasticity of the intracellular plant pathogen and insect symbiont ‘Candidatus Liberibacter asiaticus’ as revealed by hypervariable prophage genes with intragenic tandem repeats. Applied and Environmental Microbiology, 77, 6663–6673.CrossRefPubMedPubMedCentralGoogle Scholar
  46. Zhou, L., Powell, C. A., Li, W., Irey, M., & Duan, Y.-P. (2013). Prophage-mediated dynamics of ‘Candidatus Liberibacter asiaticus’ populations, the destructive bacterial pathogens of citrus Huanglongbing. PLoS One, 8(12).Google Scholar

Copyright information

© Koninklijke Nederlandse Planteziektenkundige Vereniging 2019

Authors and Affiliations

  • Larissa Bonevaes de Paula
    • 1
  • Hong Lin
    • 2
  • Eduardo Sanches Stuchi
    • 3
  • Carolina Sardinha Francisco
    • 4
  • Nágela Gomes Safady
    • 5
  • Helvécio Della Coletta-Filho
    • 5
    Email author
  1. 1.Campus de Jaboticabal, Graduate Program in Genetics and Plant BreedingUniversity of Estadual Paulista - UNESPJaboticabalBrazil
  2. 2.USDA / San Joaquin Valley Agricultural Sciences CenterParlierUSA
  3. 3.Estação Experimental de Citricultura de Bebedouro/EMBRAPABebedouroBrazil
  4. 4.Plant Pathology, Institute of Integrative BiologyETH ZürichZürichSwitzerland
  5. 5. Instituto Agronômico (IAC)/Centro de Citricultura Sylvio MoreiraCordeirópolisBrazil

Personalised recommendations