Yaping Hu1,2,3, Zhiyong Xi4, Xiaobo Liu5, Jun Wang5, Yuhong Guo5, Dongsheng Ren5, Haixia Wu5, Xiaohua Wang6, Bin Chen7, Qiyong Liu8. 1. State Key Laboratory of Infectious Disease Prevention and Control, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, WHO Collaborating Centre for Vector Surveillance and Management, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, 102206, People's Republic of China. huyap9009@163.com. 2. Nanjing Institute of Environmental Sciences, Ministry of Ecology and Environment of the People's Republic of China, Nanjing, China. huyap9009@163.com. 3. Institute of Entomology and Molecular Biology, College of Life Sciences, Chongqing Normal University, Chongqing, China. huyap9009@163.com. 4. Key Laboratory of Tropical Disease Control of the Ministry of Education, Sun Yat-sen University-Michigan State University Joint Center of Vector Control for Tropical Diseases, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, China. 5. State Key Laboratory of Infectious Disease Prevention and Control, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, WHO Collaborating Centre for Vector Surveillance and Management, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, 102206, People's Republic of China. 6. Haikou Center for Disease Control and Prevention, Haikou, China. 7. Institute of Entomology and Molecular Biology, College of Life Sciences, Chongqing Normal University, Chongqing, China. c_bin@hotmail.com. 8. State Key Laboratory of Infectious Disease Prevention and Control, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, WHO Collaborating Centre for Vector Surveillance and Management, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, 102206, People's Republic of China. liuqiyong@icdc.cn.
Abstract
BACKGROUND: Aedes albopictus is naturally infected with Wolbachia spp., maternally transmitted bacteria that influence the reproduction of hosts. However, little is known regarding the prevalence of infection, multiple infection status, and the relationship between Wolbachia density and dengue outbreaks in different regions. Here, we assessed Wolbachia infection in natural populations of Ae. albopictus in China and compared Wolbachia density between regions with similar climates, without dengue and with either imported or local dengue. RESULTS: To explore the prevalence of Wolbachia infection, Wolbachia DNA was detected in mosquito samples via PCR amplification of the 16S rRNA gene and the surface protein gene wsp. We found that 93.36% of Ae. albopictus in China were positive for Wolbachia. After sequencing gatB, coxA, hcpA, ftsZ, fbpA and wsp genes of Wolbachia strains, we identified a new sequence type (ST) of wAlbB (464/465). Phylogenetic analysis indicated that wAlbA and wAlbB strains formed a cluster with strains from other mosquitoes in a wsp-based maximum likelihood (ML) tree. However, in a ML tree based on multilocus sequence typing (MLST), wAlbB STs (464/465) did not form a cluster with Wolbachia strains from other mosquitoes. To better understand the association between Wolbachia spp. and dengue infection, the prevalence of Wolbachia in Ae. albopictus from different regions (containing local dengue cases, imported dengue cases and no dengue cases) was determined. We found that the prevalence of Wolbachia was lower in regions with only imported dengue cases. CONCLUSIONS: The natural prevalence of Wolbachia infections in China was much lower than in other countries or regions. The phylogenetic relationships among Wolbachia spp. isolated from field-collected Ae. albopictus reflected the presence of dominant and stable strains. However, wAlbB (464/465) and Wolbachia strains did not form a clade with Wolbachia strains from other mosquitoes. Moreover, lower densities of Wolbachia in regions with only imported dengue cases suggest a relationship between fluctuations in Wolbachia density in field-collected Ae. albopictus and the potential for dengue invasion into these regions.
BACKGROUND:Aedes albopictus is naturally infected with Wolbachia spp., maternally transmitted bacteria that influence the reproduction of hosts. However, little is known regarding the prevalence of infection, multiple infection status, and the relationship between Wolbachia density and dengue outbreaks in different regions. Here, we assessed Wolbachia infection in natural populations of Ae. albopictus in China and compared Wolbachia density between regions with similar climates, without dengue and with either imported or local dengue. RESULTS: To explore the prevalence of Wolbachia infection, Wolbachia DNA was detected in mosquito samples via PCR amplification of the 16S rRNA gene and the surface protein gene wsp. We found that 93.36% of Ae. albopictus in China were positive for Wolbachia. After sequencing gatB, coxA, hcpA, ftsZ, fbpA and wsp genes of Wolbachia strains, we identified a new sequence type (ST) of wAlbB (464/465). Phylogenetic analysis indicated that wAlbA and wAlbB strains formed a cluster with strains from other mosquitoes in a wsp-based maximum likelihood (ML) tree. However, in a ML tree based on multilocus sequence typing (MLST), wAlbB STs (464/465) did not form a cluster with Wolbachia strains from other mosquitoes. To better understand the association between Wolbachia spp. and dengue infection, the prevalence of Wolbachia in Ae. albopictus from different regions (containing local dengue cases, imported dengue cases and no dengue cases) was determined. We found that the prevalence of Wolbachia was lower in regions with only imported dengue cases. CONCLUSIONS: The natural prevalence of Wolbachia infections in China was much lower than in other countries or regions. The phylogenetic relationships among Wolbachia spp. isolated from field-collected Ae. albopictus reflected the presence of dominant and stable strains. However, wAlbB (464/465) and Wolbachia strains did not form a clade with Wolbachia strains from other mosquitoes. Moreover, lower densities of Wolbachia in regions with only imported dengue cases suggest a relationship between fluctuations in Wolbachia density in field-collected Ae. albopictus and the potential for dengue invasion into these regions.
Dengue is a rapidly spreading infectious disease transmitted between humans by mosquitoes of the genus Aedes. It is estimated that 400 million people are infected with dengue per year worldwide. To date, no effective vaccine or curative antiviral drug is available to prevent or treat dengue fever [1]. Thus, vector control has become the primary tool for dengue intervention. In China, Aedes albopictus is the primary dengue vector, and was responsible for the epidemic in 2014 resulting in approximately 47,000 infections. Use of insecticides is effective in controlling dengue, but is often prohibitively expensive, unsustainable and environmentally unfriendly. Other approaches require constant interventions that are expensive and difficult to implement in urban areas [2]. In recent years, the Wolbachia-based approach has been proposed as a new vector control strategy [3].Wolbachia is a genus of Gram-negative bacteria that infect arthropods and filarial nematodes. It has been recently estimated that ~ 40% of arthropod species and ~ 28.1% of mosquitoes are infected with Wolbachia [4, 5]. These alpha-proteobacteria endosymbionts are transmitted vertically through host eggs and alter host biology in diverse ways, including reproductive manipulations such as feminization, parthenogenesis, male killing and sperm-egg incompatibility [6-8]. Furthermore, a large number of studies have shown that Wolbachia have an effect on the host’s olfactory sense, immunity and lifespan [9, 10]. After Hedges et al. [11] and Teixeira et al. [12] reported that Wolbachia can protect Drosophila flies from viral infections, a novel control strategy was proposed using Wolbachia to control or limit the spread of mosquito-transmitted diseases such as dengue and malaria. A Wolbachia strain from Drosophila could be transferred into Aedes aegypti; releasing this transinfected mosquito may result in invasion and spread of Wolbachia into wild mosquito populations [13]. Additionally, these strains also interfere with the host’s reproduction, inhibit viral replication and reduce adult lifespan [14].wMel-transinfected Ae. aegypti populations have already been established and successfully released in Australia [3, 15]. Subsequently, other countries and regions in which Ae. aegypti is the main vector of dengue, such as Vietnam, Brazil, Colombia and Indonesia, have also started to release wMel-infected mosquitoes [16, 17]. In different parts of China, especially the south (e.g. Guangdong), Ae. albopictus is the major vector of dengue. Thus, studies are currently underway to apply a Wolbachia strain, wPip, from a Culex mosquito species to control Ae. albopictus. Although the theory and technology are already established, the prevalence and characteristics of Wolbachia in natural Ae. albopictus populations are poorly understood.Aedes albopictus carries Wolbachia superinfections with two strains, wAlbA and wAlbB. In a given region Ae. albopictus harbors only single wAlbA infections, and field-collected mosquitoes with single wAlbB infections were identified in Changsha, Chenzhou and Wuhan, as has been previously reported in Guangzhou [18]. Studies of natural Wolbachia infections of Ae. albopictus in China have been much less conclusive and were mainly based on the wsp gene. In addition, multilocus sequence typing (MLST), a robust classification system that accomplishes strain typing based on variation in five conserved housekeeping genes (ftsZ, gatB, coxA, hcpA and fbpA), was applied in mosquitoes singly infected with supergroup A or B Wolbachia [19]. No studies have applied MLST to assess co-infection with supergroups A and B Wolbachia in Ae. albopictus. In previous studies, quantification of Wolbachia in mosquitoes aimed to examine the direct association between Wolbachia and virus in vivo, and several studies were carried out to understand virus-Wolbachia relationships in natural mosquito populations [20, 21].The present study aimed to determine the natural prevalence of Wolbachia infections and to investigate differences in Wolbachia infection among five different climatic regions. MLST and wsp analyses were applied to characterize Wolbachia strains and estimate the phylogenetic relationships between Wolbachia strains in field-collected Ae. albopictus from China. Our findings illuminate the characteristics and prevalence of Wolbachia in natural populations of Ae. albopictus in China.
Methods
Mosquito sampling
According to the geographical distribution and climatic characteristics of Ae. albopictus in China, we selected 6–8 sites in each of five climate zones of Ae. albopictus distribution. Samples were collected at each site according to a five-point method. In this study, a total of 704 adult Ae. albopictus (190 males and 514 females) were collected from 34 districts between June and October 2014 (Table 1). For analysis of prevalence, sampling locations were placed into five climate groups as defined in the Chinese Climatic Regions, based on the following climate classifications: Edge of tropical; South subtropical; Mid-subtropical; North subtropical; and Warm temperate zone (Fig. 1) [22]. BG traps, human baited net traps and manual aspirators were used to catch adult mosquitoes. Pipettes and dippers were used for capturing larvae or pupae from different containers at each site. The same operation was repeated at least five times in each location to reduce sampling error. Sampling staff were well protected whilst catching adults to avoid mosquito bites. The collected larvae and pupae were reared to adults and supplemented with yeast extract. The adults collected in the field were examined morphologically to confirm whether they were Ae. albopictus [23]. Samples were stored at − 80 °C in individual tubes containing 95% ethanol until DNA extraction.
Table 1
Sample information
Climate zone
District
Coordinates
No. of samples
♀
♂
Edge of tropical
Wenchang
19.57°N, 110.80°E
33
25
8
Wanning
18.81°N, 110.39°E
21
16
5
Haikou
20.02°N, 110.20°E
33
21
12
Qiongzhong
19.04°N, 109.83°E
18
10
8
Sanya
18.25°N, 109.51°E
37
22
15
Jinghong
22.01°N, 100.77°E
34
23
11
Dehong
24.43°N, 98.59°E
21
19
2
South subtropical
Nanning
22.82°N, 108.36°E
25
17
8
Foshan
23.02°N, 113.11°E
12
10
2
Guangzhou
23.41°N, 113.23°E
33
19
14
Jiangmen
22.50°N, 113.40°E
5
2
3
Zhongshan
22.40°N, 112.72°E
20
12
8
Fuzhou
26.08°N, 119.30°E
24
18
6
Xiamen
24.59°N, 118.10°E
24
15
9
Mid-subtropical
Changsha
28.21°N, 112.99°E
25
11
14
Chenzhou
25.77°N, 113.01°E
18
13
5
Nanchang
28.68°N, 115.86°E
22
16
6
Chengdu
30.66°N, 104.07°E
18
14
4
Nanchong
30.49°N, 106.04°E
2
1
1
Chongqing
29.57°N, 106.55°E
24
24
24
North subtropical
Hefei
31.82°N, 117.23°E
9
8
1
Nanjing
32.05°N, 118.79°E
27
20
7
Shanghai
31.23°N, 121.48°E
31
24
7
Wuhan
30.35°N, 114.17°E
6
2
4
Wuxi
31.34°N, 120.18°E
3
3
0
Hangzhou
30.18°N, 119.5°E
26
18
8
Warm temperate zone
Beijing
39.77°N, 116.66°E
30
24
6
Shangqiu
34.17°N, 116.20°E
13
13
0
Taiyuan
37.98°N, 112.32°E
31
31
0
Xian
34.17°N, 108.21°E
18
18
0
Tangshan
39.96°N, 118.81°E
3
2
1
Kaifeng
34.80°N, 114.27°E
15
12
3
Tianshui
34.71°N, 105.47°E
22
20
2
Dalian
38.94°N, 121.40°E
21
15
6
Fig. 1
Distribution of sampling sites for Ae. albopictus. Black, red, pink, purple, and brown dots are the sample sites at the Edge of tropical, South subtropical, Mid-subtropical, North subtropical and Warm temperate zones, respectively
Sample informationDistribution of sampling sites for Ae. albopictus. Black, red, pink, purple, and brown dots are the sample sites at the Edge of tropical, South subtropical, Mid-subtropical, North subtropical and Warm temperate zones, respectively
DNA extraction and prevalence of Wolbachia infection
To assess the prevalence of Wolbachia infection, 2–37 Ae. albopictus were used from each population to extract total DNA. After drying the Ae. albopictus for several minutes, they were washed three times in ddH2O. DNA was then individually extracted using a DNAeasy Tissue Kit (Qiagen, Valencia, CA, USA). Two 16S rDNA primers and four wsp-specific primers, WAF/WAR and WBF/WBR, were used to detect Wolbachia DNA by polymerase chain reaction (PCR) using the DNA of a single mosquito as a template [24, 25]. The 28S rRNA gene was used to assess the quality of DNA extraction and the cox1 mitochondrial gene was sequenced to exclude mosquitoes that were not Ae. albopictus. The full-length cox1 gene was amplified using four primers, cox1F/cox1R and cox1f/cox1r (Table 2). PCR reactions were performed in a final volume of 25 μl containing 2 μl of DNA, 11 μl of ddH2O, 1 μM of each primer and 10 μl of SuperMix. The temperature was cycled at 94 °C for 2 min, followed by 37 cycles of 94 °C for 30 s, 55 °C for 45 s and 72 °C for 1 min, and then a final extension step at 72 °C for 10 min. DNA extracted from Wolbachia-infectedAe. albopictus was used as a positive control and ddH2O was used as a negative control. PCR products were run on 1% agarose gels and the cox1 PCR products were sequenced directly.
Table 2
Primers for amplification and sequencing
Gene
Primer
Sequence (5′–3′)
Annealing T (°C)
16S rDNA
16SF
CGGGGGAAAAATTTATTGCT
55
16SR
AGCTGTAATACAGAAAGTAAA
wAlbA-wsp
WAF
CCAGCAGATACTATTGCG
55
WAR
AAAAATTAAACGCTACTCCA
wAlbB-wsp
WBF
AAGGAACCGAAGTTCATG
55
WBR
AAAAATTAAACGCTACTCCA
wsp
81
TGGTCCAATAAGTGATGAAGAAAC
53
691
AAAAATTAAACGCTACTCCA
FtsZ
ftsZ-F
TACTGACTGTTGGAGTTGTAACTAAGCCGT
58
ftsZ-R
TGCCAGTTGCAAGAACAGAAACTCTAACTC
28S rRNA
28F
TACCGTGAGGGAAAGTTGAAA
55
28R
AGACTCCTTGGTCCGTGTTT
cox1
cox1F
TTTACAATTTATCGCCTAAACTTC
55
cox1R
CATTGCACTAATCTGCCATA
cox1f
GGGGGAGACCCTATTTTATA
55
cox1r
TAAACTTCAGGGTGACCAAAAAATCA
wAlbAq-wsp
qAF
GGGTTGATGTTGAAGGAG
55
qAR
CACCAGCTTTTACTTGACC
wAlbBq-wsp
qBF
ACGTTGGTGGTGCAACATTTG
58
qBR
TAACGAGCACCAGCATAAAGC
RPS
RPS6-F
CGTCGTCAGGAACGTATTCG
55
RPS6-R
TCTTGGCAGCCTTGACAGC
Note: Primers cox1f/cox1r were used for sequencing
Abbreviation: T, temperature
Primers for amplification and sequencingNote: Primers cox1f/cox1r were used for sequencingAbbreviation: T, temperature
Cloning and sequencing of wsp and MLST genes
The WSP loci were amplified with wsp (Wolbachia surface protein gene) primers to confirm multiple infections. PCR reactions were performed in a final volume of 25 μl containing 2 μl of DNA, 11 μl of ddH2O, 1 μM of each primer and 10 μl of SuperMix. The temperature was cycled at 94 °C for 2 min, followed by 37 cycles of 94 °C for 30 s, 53 °C for 45 s and 72 °C for 1 min, and then a final extension step at 72 °C for 10 min.The five MLST loci were amplified according to previously published protocols (http://pubmlst.org/Wolbachia/). PCR reactions were performed in a final volume of 25 μl containing 2 μl of DNA, 11 μl of ddH2O, 1 μM of each primer and 10 μl of SuperMix. The temperature was cycled at 94 °C for 2 min, followed by 37 cycles of 94 °C for 30 s, Tm (Tm values for each primer pair are shown in Table 2) for 45 s and 72 °C for 90 s, and then a final extension step at 72 °C for 10 min. For co-infected samples, the coxA and ftsZ genes were amplified using primers coxA_F1 (5′-TTG GRG CRA TYA ACT TTA TAG-3′) and coxA_R1 (5′-CT AAA GAC TTT KAC RCC AGT-3′), and ftsZ-F (5′-TAC TGA CTG TTG GAG TTG TAA CTA AGC CGT-3′) and ftsZ-R (5′-TGC CAG TTG CAA GAA CAG AAA CTC TAA CTC-3′), respectively. For the fragment of coxA, primers for B-specific MLST protocols for AB infections were not used in our study, and ftsZ fragments were not long enough to be amplified by A-specific and B-specific primers. Fragments of coxA, ftsZ and wsp with the expected sizes were excised from the gel and purified using the Pure Yield™ Plasmid Miniprep System (Promega, Madison, USA). The purified DNA was ligated into pEASY-T5 Zero Cloning vector (Trans) and then transferred to Trans1-T1 phage resistant chemically competent cells (Trans). Putative clones of expected fragments were submitted for DNA sequencing. For all three kinds of fragments, at least eight clones were sequenced for each mosquito using both M13 forward and reverse primers, with three individuals being analyzed for each geographical population.
Nucleotide sequence accession numbers
All newly generated sequences for wsp, cox1, gatB, coxA, hcpA, ftsZ, fbpA genes were deposited in the GenBank database under accession numbers KU738304-KU738385, KU738386-KU738431, MK809569-MK809640, MK809709-MK809776, MK809845-MK809912, MK809777-MK809844, MK809641-MK809708, respectively. According to the MLST protocol, the sequences of gatB, coxA, hcpA, ftsZ, fbpA and wsp were submitted to the PubMLST database for sequence typing, generating a MLST allelic profile and a WSP hypervariable region (HVR) profile. Strain and host information were deposited in the MLST database.
Sequence typing and phylogenetic analyses
For Wolbachia-specific wsp gene sequence analysis, several reported sequences with similarities of > 97% were obtained from GenBank for comparisons. The wsp sequence of Brugia malayi was selected as the outgroup. We also analyzed co-infection with different Wolbachia species. Furthermore, a reference list of Wolbachia isolates was constructed by searching the MLST database, which was selected for having a complete set of MLST and HVR profiles. A total of 40 of known STs were from supergroup A, supergroup B, supergroup D and supergroup F Wolbachia, and supergroup D (Table 3) and supergroup F Wolbachia were selected as outgroups. Allele sequences were downloaded from the MLST database and these Wolbachia sequences were manually edited with Chromas2.4 by DNAMAN and their translated amino acid sequences were aligned using MUSCLE in MEGA6.0. Then, the concatenated data set of the five MLST genes was subjected to a phylogenetic analysis using MEGA 6.0. The wsp sequences were also subjected to a phylogenetic analysis using MEGA 6.0 using supergroup D and F Wolbachia strains as outgroups (for consistency with the MLST-based analysis). Maximum likelihood (ML) methods in MEGA 6.0 were used to analyze phylogenetic relationships. To select the optimal evolutionary model by critically evaluating the selected parameters, Find Best-Fit Substitution Model was conducted in MEGA 6.0 [26]. For the NCBI-wsp sequences, the concatenated dataset and the wsp sequences, the submodels T92 (Tamura 3-parameter), GTR+I+G and T92 (Tamura 3-parameter)+G were selected, respectively. The ML trees were constructed with 1000 bootstrap replicates.
Table 3
MLST allelic and WSP profiles of Wolbachia subjected for phylogenetic analyses
ID
Supergroup
Host species
ST
gatB
coxA
hcpA
ftsZ
fbpA
wsp
HVR1
HVR2
HVR3
HVR4
1
A
Drosophila melanogaster
1
1
1
1
1
1
31
1
12
21
24
12
A
Aedes albopictus
2
3
2
2
10
3
1
1
1
1
1
496
A
Aedes bromeliae
304
182
160
187
148
232
114
A
Notoncus sp.
53
46
42
23
6
17
49
9
9
12
9
120
A
Camponotus leonardi
57
49
44
53
42
49
52
41
42
45
42
167
A
Agelenopsis aperta
67
35
35
22
33
39
43
31
32
35
34
294
A
Asobara japonica
370
87
111
103
70
186
530
188
213
15
25
399
A
Apanteles chilonis
260
172
150
7
137
8
592
209
15
17
14
1682
A
Syrphophilus asperatus
433
234
84
257
200
120
689
11
9
267
302
56
A
Rhagoletis cerasi
13
1
1
1
3
1
23
1
12
21
11
2
A
Solenopsis invicta
29
19
20
22
17
20
28
21
21
25
21
61
A
Rhagoletis cerasi
159
53
84
85
70
79
113
67
77
12
9
68
A
Agelenopsis aperta
65
32
33
38
30
37
38
28
29
33
32
88
A
Drosophila testacea
99
10
72
11
14
11
13
1
11
21
11
107
A
Wasmannia Peru
47
43
20
46
38
46
28
21
21
25
21
96
A
Aganaspis alujai
164
54
52
62
82
62
75
11
9
15
25
129
A
Dorymyrmex elegans
63
19
21
55
46
53
51
42
43
47
25
325
A
Ephestia kuehniella
92
54
59
68
3
67
83
51
55
15
57
413
A
Chelonus munakatae
19
7
6
7
3
8
599
2
191
192
248
29
B
Culex pipiens
9
4
3
3
22
4
10
10
8
10
8
499
B
Mansonia africana
305
9
38
189
36
4
19
B
Chelymorpha alternans
7
9
14
15
12
14
8
7
7
8
7
22
B
Acraea encedon
3
9
11
12
11
12
2
2
2
2
2
27
B
Drosophila simulans
16
5
4
4
4
5
15
10
8
11
13
34
B
Nasonia vitripennis
26
9
8
9
7
9
25
18
16
23
16
99
B
Horaga onyx
39
12
14
13
2
41
65
34
36
3
23
118
B
Pheidole sciophila
56
48
43
52
41
6
60
40
41
43
41
408
B
Apanteles chilonis
271
9
150
7
142
4
593
18
79
237
16
269
B
Diaphorina Diaphorina citri
175
109
86
88
126
27
160
2
17
3
23
39
B
Lycaeides idas
36
9
36
40
7
9
61
18
16
23
16
73
B
Lycaeides melissa
162
108
73
40
80
9
294
125
141
127
102
70
B
Rhagoletis cerasi
160
101
85
40
22
4
116
69
17
3
23
40
B
Hypolimnas bolina
125
4
14
40
73
4
10
10
8
10
8
87
B
Drosophila innubila
98
79
71
88
69
27
82
2
35
98
23
97
B
Anthene emolus
37
9
9
6
8
10
63
19
17
24
33
200
B
Eurema mandarina
40
38
38
29
35
42
64
35
35
38
44
311
B
Sogatella furcifera
213
106
11
13
105
162
463
2
191
192
22
315
B
Macrosteles fascifrons
217
135
120
141
108
197
536
191
220
23
16
37
D
Brugia malayi
35
28
29
33
26
30
34
24
24
27
26
36
F
Cimex lectularius
8
26
27
31
24
28
7
6
6
7
6
MLST allelic and WSP profiles of Wolbachia subjected for phylogenetic analyses
wAlbA and wAlbB Wolbachia strain quantitation
Twenty-eight mosquitoes from regions with local dengue cases (Guangzhou and Jinghong), with only imported cases (Xiamen and Haikou) and without dengue cases (Wenchang and Fuzhou) were amplified individually by quantitative PCR using strain-specific primers qAF/qAR [27] and qBF/qBR (Table 2) to examine the relationship between Wolbachia density in field-collected Ae. albopictus and the presence of dengue virus. The Bio-Rad CFX96 Real-Time PCR Detection System (Hercules, USA) and GoTaq® qPCR Master Mix (Promega) were used in our study. PCR reactions were performed in a final volume of 20 µl containing 10 µl of GoTaq® qPCR Master Mix, 0.5 µM of each primer, 2 µl of template DNA and 7 µl of RNase-free water. Reactions were mixed with an electronic pipette. The thermal cycling conditions were: 10 min at 95 °C, followed by 50 cycles of 94 °C for 15 s, primer Tm (wAlbA 55 °C, wAlbB 58 °C and RPS6 55 °C) for 30 s, 72 °C for 30 s, and finally 72 °C (read temperature) for 15 s. The melting curve was constructed between 49 °C and 63 °C. We used a serial dilution of pEASY®-T5 Zero Cloning vectors containing one copy each of RPS6 [28], wAlbAq-wsp and wAlbBq-wsp gene fragments, and used their primers set up in each PCR to plot standard curves, in case any binding efficiency difference appeared. Every mosquito DNA template was quantified three times for each of the RPS6, wAlbAq-wsp and wAlbBq-wsp genes. Assuming that each gene was present in a single copy per haploid genome, the ratio between wsp and RPS6 provided the number of Wolbachia genomes relative to the number of Aedes genomes [29].
Statistical analysis
To compare the densities of the two Wolbachia strains in field mosquitoes in five regions (with different adult sizes), data were normalized to the expression of the host rps6 gene. Analyses were carried out using SPSS Statistics (17.0). Chi-square tests were performed to compare the prevalence of Wolbachia infections and one-way analysis of variance (ANOVA) was performed to compare densities of Wolbachia from different regions for normally distributed data using SPSS Statistics (17.0). Differences were considered statistically significant when P < 0.05. For better presentation of results, locA and locB were used to denote the densities of supergroup A and supergroup B, respectively, from regions with local dengue cases; impA and impB were used to denote the densities of supergroup A and supergroup B, respectively, from regions with only imported dengue cases; and noA and noB were used to denote the densities of supergroup A and supergroup B, respectively, from regions with no dengue cases.
Results
Prevalence of Wolbachia infections
A total of 693 adult Ae. albopictus were obtained from five different climatic regions in China and were examined for Wolbachia infection status. Of these, 93.36% (647/693) were PCR-positive for Wolbachia using wsp and 16S rDNA primers [30]. The quality of extracted DNA was good, and the samples were all identified as Ae. albopictus [31]. Specific primers for wAlbA and wAlbB, derived from the rapidly evolving wsp outer-surface protein gene of Wolbachia, were used to screen for these bacteria in Ae. albopictus mosquitoes. The PCR results showed that 83.26% (577/693) of the mosquitoes sampled were infected with supergroup A and 91.05% (631/693) were infected with supergroup B Wolbachia strains. The prevalence of co-infection was 80.95% (561/693). Individuals singly infected with supergroup A and supergroup B Wolbachia represented 2.31% (16/693) and 10.10% (70/693) of all mosquitoes, respectively. We also found 46 uninfected individuals (Table 4).
Table 4
Infection status of Wolbachia based on PCR results of field-collected Ae. albopictus adults
Climate region
Total
No. of infected (%)
Single A
Single B
A and B
W+
Edge of tropical
186
11 (5.91)
26 (13.98)
135 (72.58)
172 (92.47)
South subtropical
143
1 (0.70)
15 (10.49)
117 (81.82)
133 (93.01)
Mid-subtropical
109
1 (0.92)
13 (11.93)
80 (73.39)
94 (86.24)
North subtropical
102
2 (1.96)
12 (11.76)
85 (83.33)
99 (97.06)
Warm temperate zone
153
1 (0.65)
4 (2.61)
144 (94.12)
149 (97.39)
Total
693
16 (2.31)
70 (10.10)
561 (80.95)
647 (93.36)
Note: W+ represents the positive rate of Wolbachia in Ae. albopictus
Infection status of Wolbachia based on PCR results of field-collected Ae. albopictus adultsNote: W+ represents the positive rate of Wolbachia in Ae. albopictusThe natural prevalence of Wolbachia infection in 34 different locations of the five climatic regions is presented in Fig. 1. Chi-square tests of Wolbachia prevalence among the five different climate regions (Fig. 2) revealed a significant difference (χ2 = 15.438, df = 4, P = 0.004). Similarly, the prevalence of supergroup A and B Wolbachia differed significantly among the five climate regions (χ2 = 24.199, df = 4, P < 0.0001 and χ2 = 17.390, df = 4, P = 0.0020, respectively). Further analysis showed that the prevalence of Wolbachia infection was significantly different in four regions: Edge of tropical vs Warm temperate zone (χ2 = 4.029, df = 1, P = 0.045); Mid-subtropical vs North subtropical (χ2 = 7.906, df = 1, P = 0.005); and Mid-subtropical vs Warm temperate zone (χ2 = 11.759, df = 1, P = 0.001). However, the prevalence of Wolbachia infection in the South subtropical region did not show any significant differences compared with any of the other four regions. For the prevalence of supergroup A Wolbachia, significant differences were detected for five regions: Edge of tropical vs Warm temperate zone (χ2 = 18.298, df = 1, P < 0.0001); South subtropical vs Warm temperate zone (χ2 = 11.204, df = 1, P = 0.001); Mid-subtropical vs North subtropical (χ2 = 3.917, df = 1, P = 0.048); Mid-subtropical vs Warm temperate zone (χ2 = 22.480, df = 1, P < 0.0001); and North subtropical vs Warm temperate zone (χ2 = 6.698, df = 1, P = 0.010). For supergroup B Wolbachia, significant differences were observed in four regions: Edge of tropical vs North subtropical (χ2 = 5.147, df = 1, P = 0.023); Edge of tropical vs Warm temperate zone (χ2 = 10.770, df = 1, P = 0.001); Mid-subtropical vs North subtropical (χ2 = 5.620, df = 1, P = 0.018); and Mid-subtropical vs Warm temperate zone (χ2 = 11.242, df = 1, P = 0.001). Similar to the overall prevalence of Wolbachia infections, the south subtropical region did not show any substantial difference compared with any of the other four regions (Figs. 2, 3).
Fig. 2
Infection rates for different sites in the Edge of tropical, South subtropical, Mid-subtropical, North subtropical and Warm temperate zones. Black, red, pink, purple and brown dots are the sample sites at the edge of Tropical, South subtropical, Mid-subtropical, North subtropical and Warm temperate zones, respectively. Blue square A, rate of single-infected with wAlbA mosquitoes; brown square B, rate of single-infected with wAlbB mosquitoes; green square AB, rate of co-infected with wAlbA and wAlbB mosquitoes; purple square N, rate of Wolbachia-negative mosquitoes
Fig. 3
Wolbachia infection rates in Ae. albopictus of the five climate regions in China: 1, Edge of tropical; 2, South subtropical; 3, Mid-subtropical; 4, North subtropical; 5, Warm temperate zone. Blue bars (A), wAlbA infection rate in Ae. albopictus; brown bars (B), wAlbB infection rate in Ae. albopictus; green bars (W), rate of co-infection with wAlbA and wAlbB in Ae. albopictus
Infection rates for different sites in the Edge of tropical, South subtropical, Mid-subtropical, North subtropical and Warm temperate zones. Black, red, pink, purple and brown dots are the sample sites at the edge of Tropical, South subtropical, Mid-subtropical, North subtropical and Warm temperate zones, respectively. Blue square A, rate of single-infected with wAlbA mosquitoes; brown square B, rate of single-infected with wAlbB mosquitoes; green square AB, rate of co-infected with wAlbA and wAlbB mosquitoes; purple square N, rate of Wolbachia-negative mosquitoesWolbachia infection rates in Ae. albopictus of the five climate regions in China: 1, Edge of tropical; 2, South subtropical; 3, Mid-subtropical; 4, North subtropical; 5, Warm temperate zone. Blue bars (A), wAlbA infection rate in Ae. albopictus; brown bars (B), wAlbB infection rate in Ae. albopictus; green bars (W), rate of co-infection with wAlbA and wAlbB in Ae. albopictus
Nucleotide sequence analysis of Wolbachia from Ae. albopictus
DNA sequencing analysis indicated that Ae. albopictus from different locations in China harbored two different Wolbachia strains: wAlbA and wAlbB (Fig. 4). The WSP profiles of wAlbA and wAlbB for wsp, HVR1, HVR2, HVR3 and HVR4 were 1, 1, 1, 1 and 1, and 169, 10, 82, 10 and 84, respectively, suggesting that these two Wolbachia strains were very stable.
Fig. 4
Maximum likelihood phylogenetic tree based on wsp gene sequences for Wolbachia from different hosts from GenBank. Red dots indicate reported Wolbachia strains of mosquitoes; green dots indicate Wolbachia strains of Ae. albopictus sampled in the present study
Maximum likelihood phylogenetic tree based on wsp gene sequences for Wolbachia from different hosts from GenBank. Red dots indicate reported Wolbachia strains of mosquitoes; green dots indicate Wolbachia strains of Ae. albopictus sampled in the present studyPhylogenetic analysis based on the concatenated sequences of all MLST loci showed that ST-2 was wAlbA, but no closely-related STs were identified for wAlbB. We submitted our sequences to the MLST database, and received new ST codes (ST-464, ST-465, designated for wAlbB1, wAlbB2 respectively). wAlbB1 and wAlbB2 only differed by a single base pair: gatB16A and gatB16G, respectively. The five MLST genes of wAlbA shared the same alleles as ST-2, as previously demonstrated [19]; however, three of the five MLST genes (fbpA, gatB and hcpA) of wAlbB1 and two of the five genes (fbpA and hcpA) of wAlbB2 shared alleles with other STs. In total, 40 known Wolbachia STs in the MLST database (http://pubmlst.org/Wolbachia/) were used as a dataset to infer the phylogeny of Wolbachia infecting field-collected Ae. albopictus. The MLST-based ML tree (Fig. 5) separated the isolates into three major clusters: supergroup A, supergroup B, and supergroup D + supergroup F. For the wsp-based ML tree, the isolates were separated into supergroup A, supergroup D, supergroup F and a mixture of supergroup A and supergroup B branches. According to these data, it was safe to classify ST-464 and ST-465 as strains of supergroup B. In the wsp-based ML tree (Fig. 6), wAlbA and wAlbB formed a cluster with strains from other mosquito species (Culex quinquefasciatus and Culex gelidus). Similarly, in the MLST-based tree, wAlbA (ST-2) formed a clade with ST-304 whose host is Aedes bromeliae. In supergroup B, wAlbB (ST-464 and ST-465) did not form a clade with ST-305 and ST-9, whose hosts were Mansonia africana and Culex pipiens, respectively (Figs. 5, 6).
Fig. 5
MLST-based maximum likelihood tree for Wolbachia from different hosts. Red dots indicate reported Wolbachia strains of mosquitoes; green dots indicate Wolbachia strains of Ae. albopictus sampled in the present study
Fig. 6
wsp-based maximum likelihood tree for Wolbachia from different hosts. Red dots indicate reported Wolbachia strains of mosquitoes; green dots indicate Wolbachia strains of Ae. albopictus sampled in the present study
MLST-based maximum likelihood tree for Wolbachia from different hosts. Red dots indicate reported Wolbachia strains of mosquitoes; green dots indicate Wolbachia strains of Ae. albopictus sampled in the present studywsp-based maximum likelihood tree for Wolbachia from different hosts. Red dots indicate reported Wolbachia strains of mosquitoes; green dots indicate Wolbachia strains of Ae. albopictus sampled in the present studyThe relative densities of the wAlbA and wAlbB strains were estimated for individual females sampled from regions with local dengue cases, with only imported dengue cases, and without dengue cases. The data were normalized using the host rps6 gene, which also allowed the densities of the two Wolbachia strains to be compared between different adult sizes.Figure 7 shows a higher density of the wAlbB strain relative to wAlbA, and this difference was significant in three different regions: locA vs locB (ANOVA, F(1, 54) = 67.143, P < 0.0001), impA vs impB (ANOVA, F(1, 54) = 38.955, P < 0.0001), and noA vs noB (ANOVA, F(1,54) = 12.650, P = 0.001). Moreover, both wAlbA and wAlbB strains showed significantly lower densities in regions with only imported dengue cases than in the other two regions [wAlbA (ANOVA, F(2, 81) = 10.203, P < 0.0001) and wAlbB (ANOVA, F(2, 81) = 7.468, P = 0.001)]. Neither locA vs impA, locA vs noA, locB vs impB, nor locB vs noB showed any significant difference, which may indicate a relationship between the fluctuation of Wolbachia density in field Ae. albopictus and the invasion of dengue virus.
Fig. 7
Relative Wolbachia densities in Ae. albopictus collected in different regions in China. Abbreviations: loc-A, relative densities of wAlbA in the regions with local dengue cases; imp-A, relative densities of wAlbA in the regions with import dengue cases; no-A, relative densities of wAlbA in the regions without dengue cases; loc-B, relative densities of wAlbB in the regions with local dengue cases; imp-B, relative densities of wAlbB in the regions with import dengue cases; no-B, relative densities of wAlbB in the regions without dengue cases
Relative Wolbachia densities in Ae. albopictus collected in different regions in China. Abbreviations: loc-A, relative densities of wAlbA in the regions with local dengue cases; imp-A, relative densities of wAlbA in the regions with import dengue cases; no-A, relative densities of wAlbA in the regions without dengue cases; loc-B, relative densities of wAlbB in the regions with local dengue cases; imp-B, relative densities of wAlbB in the regions with import dengue cases; no-B, relative densities of wAlbB in the regions without dengue cases
Discussion
Wolbachia is a bacterial endosymbiont that infects the reproductive tissues of arthropods, mainly insects. It is spread primarily via the ova cytoplasm and alters the reproductive success of its host, thus making it a suspected driver of development and speciation. The prevalence of Wolbachia in insects has been reported as ranging from 20% to 65% [32]. Our results showed a prevalence of 93.36% for Wolbachia in natural populations of Ae. albopictus in China, slightly lower than the 100% previously reported in Guangzhou (China), Orissa (India), Chachoengsao (Thailand) [18, 33, 35] and over 99% in Korea [34]. Furthermore, single infections with both wAlbA and wAlbB were detected in our study and the prevalence of wAlbB (10.10%) strains was higher than that of wAlbA strains (2.31%). To the best of our knowledge, this is the first report of single wAlbB infections in field-collected Ae. albopictus in Changsha, Chenzhou and Wuhan, China, and our findings were similar to those reported in Guangzhou [18]. These results thus support and validate the work of O’Neill et al. [35]. In the present study, 28S rRNA was used to assess the quality of DNA extraction [30] and the cox1 gene of Ae. albopictus was sequenced to rule out samples that were not Ae. albopictus. In addition, to obtain an accurate estimate of the prevalence of wAlbA and wAlbB, qPCR was used to check negative samples and indicated an increased prevalence of 83.26% and 91.05% for supergroup A and B Wolbachia strains, respectively.Wolbachia significantly and efficiently reduced the proportions of mosquitoes achieving infection and transmission potential across the different regions. Wolbachia density is sensitive to temperature variations [36]. A Chi-square test of Wolbachia prevalence among the five different climate regions in China revealed that geographical location and climate may have a significant effect on the prevalence of Wolbachia in natural populations of Ae. albopictus. As shown in Fig. 3, for both wAlbA and wAlbB, the prevalence of Wolbachia infection in the Mid-subtropical region was lower than in other climate regions; the difference between the North subtropical region and the Warm temperate zone was apparent in all three measures of prevalence. There was a clearly lower prevalence in Chenzhou (Fig. 2), which may be the reason why rates in the Mid-subtropical region were lower than in other regions. Aside from this, the rates of Wolbachia infection did not show any linear relationships, which may imply that there is no absolute correlation between climate region and Wolbachia infection.MLST is an important source of sequence data for comparative genetics, providing a tool for exploring molecular evolutionary methods in intracellular bacteria [19]. Our results show that in both the MLST-based and wsp-based ML trees, Wolbachia isolates included in the analyses are placed in supergroups A and B (Fig. 5). However, in the wsp-based ML tree (Fig. 6), a mixed cluster of supergroups A and B was identified, with ST-19, ST29, ST47, ST65 and ST67 belonging to a supergroup associated with isolates from supergroup B. This suggests that MLST-based genotyping is perhaps more accurate than the wsp-based method. Our results may, however, be explained by the fact that the sharing of wsp sequences between A and B strain supergroups indicates a strong genetic cohesiveness of Wolbachia strains [37]. Moreover, for supergroup B in the wsp-based ML tree, Wolbachia of Ae. albopictus did not show an exact match with previously identified STs. Furthermore, we identified the new ST-464 strain wAblB1 and the new ST-465 strain wAblB2. ST-464 was found in all locations, but ST-465 strains were only found in single infected mosquitoes from Changsha and Chenzhou and co-infected mosquitoes from Wuhan and Nanchang. This may reflect the various states of Wolbachia infection in these locations.The density of the endosymbiont Wolbachia plays an important role in crossing sterility, which is known as a cytoplasmic incompatibility and limits the degree of parental spread. Aedes albopictus mosquitoes can be superinfected with the Wolbachia strains wAlbA and wAlbB [38]. In our study, the wAlbB strain was found at a higher density than wAlbA in Ae. albopictus, which is consistent with the results of two previous studies [38, 39]. To our knowledge, this study is the first to assess relative Wolbachia densities in Ae. albopictus mosquitoes from different natural populations, which were sampled from regions with different dengue fever load. The relative density of Wolbachia (wAlbA and wAlbB) in mosquitoes from regions with only imported dengue cases was lower than that in mosquitoes from regions with local dengue cases and without dengue cases. The decrease of Wolbachia density could lead to the loss of protection by the host immune system [40]. We hypothesize that the imported dengue cases caused a lowering of Wolbachia densities in natural mosquito populations and that densities of virus in these mosquitoes will increase. Sometime later, densities of virus and Wolbachia would come to a balance in the natural mosquito populations and thereafter could transmit virus smoothly, resulting in local dengue case emerging. This hypothesis has yet to be substantiated by other reports, but our results may reflect the alarm reaction of natural mosquito populations in response to invasion of dengue virus, which is embodied in the fluctuation of Wolbachia densities. Furthermore, the low prevalence in Chenzhou, which also has imported dengue cases, may be explained if our hypothesis were correct [41, 42]. Further research is needed to explore the relationship between Wolbachia densities in natural Ae. albopictus mosquitoes and the invasion of dengue virus.In this study, we obtained adult mosquitoes at a variety of ages from different parts of China. Because adults had only recently emerged (1 or 2 days), these may have had Wolbachia densities that were too low to be detected. Our subsequent studies will be based on field-collected larvae, which will be brought back to the laboratory and used for further research after emergence.
Conclusions
This study demonstrated that the natural prevalence of Wolbachia infections in China was much lower than the prevalence in other countries or regions. The prevalence of Wolbachia was significantly different among five different climatic regions. The phylogenetic relationships of Wolbachia in field-collected Ae. albopictus were estimated based on MLST and wsp analyses, and showed that these strains were rather stable. However, wAlbB (464/465) and Wolbachia strains did not form a clade with Wolbachia strains from other mosquitoes. Moreover, the lower densities of Wolbachia in regions with only imported dengue cases suggested a relationship between the fluctuation of Wolbachia density in natural Ae. albopictus populations and the invasion of dengue virus.
Authors: A A Hoffmann; B L Montgomery; J Popovici; I Iturbe-Ormaetxe; P H Johnson; F Muzzi; M Greenfield; M Durkan; Y S Leong; Y Dong; H Cook; J Axford; A G Callahan; N Kenny; C Omodei; E A McGraw; P A Ryan; S A Ritchie; M Turelli; S L O'Neill Journal: Nature Date: 2011-08-24 Impact factor: 49.962
Authors: Francesca D Frentiu; Tasnim Zakir; Thomas Walker; Jean Popovici; Alyssa T Pyke; Andrew van den Hurk; Elizabeth A McGraw; Scott L O'Neill Journal: PLoS Negl Trop Dis Date: 2014-02-20
Authors: Perran A Ross; Xinyue Gu; Katie L Robinson; Qiong Yang; Ellen Cottingham; Yifan Zhang; Heng Lin Yeap; Xuefen Xu; Nancy M Endersby-Harshman; Ary A Hoffmann Journal: Appl Environ Microbiol Date: 2021-08-11 Impact factor: 4.792