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Comparative characterization of microbiota between the sibling species of tea geometrid moth Ectropis obliqua Prout and E. grisescens Warren

Published online by Cambridge University Press:  03 August 2020

Zhibo Wang
Affiliation:
Key Laboratory of Tea Quality and Safety Control, Ministry of Agriculture, Tea Research Institute, Chinese Academy of Agricultural Sciences, Hangzhou, China
Hong Li
Affiliation:
Key Laboratory of Tea Quality and Safety Control, Ministry of Agriculture, Tea Research Institute, Chinese Academy of Agricultural Sciences, Hangzhou, China
Xiaogui Zhou
Affiliation:
Key Laboratory of Tea Quality and Safety Control, Ministry of Agriculture, Tea Research Institute, Chinese Academy of Agricultural Sciences, Hangzhou, China
Meijun Tang
Affiliation:
Key Laboratory of Tea Quality and Safety Control, Ministry of Agriculture, Tea Research Institute, Chinese Academy of Agricultural Sciences, Hangzhou, China
Liang Sun
Affiliation:
Key Laboratory of Tea Quality and Safety Control, Ministry of Agriculture, Tea Research Institute, Chinese Academy of Agricultural Sciences, Hangzhou, China
Shuai Zhan
Affiliation:
Key Laboratory of Insect Developmental and Evolutionary Biology, Institute of Plant Physiology and Ecology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai, China
Qiang Xiao*
Affiliation:
Key Laboratory of Tea Quality and Safety Control, Ministry of Agriculture, Tea Research Institute, Chinese Academy of Agricultural Sciences, Hangzhou, China
*
Author for correspondence: Qiang Xiao, E-mail: xqtea@mail.tricaas.com
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Abstract

For a wide range of insect species, the microbiota has potential roles in determining host developmental programme, immunity and reproductive biology. The tea geometrid moths Ectropis obliqua and E. grisescens are two closely related species that mainly feed on tea leaves. Although they can mate, infertile hybrids are produced. Therefore, these species provide a pair of model species for studying the molecular mechanisms of microbiotal involvement in host reproductive biology. In this study, we first identified and compared the compositions of microbiota between these sibling species, revealing higher microbiotal diversity for E. grisescens. The microbiota of E. obliqua mainly comprised the phyla Firmicutes, Proteobacteria and Cyanobacteria, whereas that of E. grisescens was dominated by Proteobacteria, Actinobacteria and Firmicutes. At the genus level, the dominant microbiota of E. grisescens included Wolbachia, Enterobacter and Pseudomonas and that of E. obliqua included Melissococcus, Staphylococcus and Enterobacter. Furthermore, we verified the rate of Wolbachia to infect 80 samples from eight different geographical populations, and the results supported that only E. grisescens harboured Wolbachia. Taken together, our findings indicate significantly different microbiotal compositions for E. obliqua and E. grisescens, with Wolbachia possibly being a curial factor influencing the reproductive isolation of these species. This study provides new insight into the mechanisms by which endosymbiotic bacteria, particularly Wolbachia, interact with sibling species.

Type
Research Paper
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited.
Copyright
Copyright © Tea Research Institute, Chinese Academy of Agricultural Sciences, 2020. Published by Cambridge University Press

Introduction

Important interactions of microbiota organisms with insects are very common in nature (Mao et al., Reference Mao, Tan, Wang, Chen, Wang, Huang and Gong2018). Some of the microbiota harboured in host cells are considered endosymbionts, constituting a symbiotic bacteriome. Other microbiota species opportunistically colonize different tissues of insects and the gut lumen, which can be affected by many factors, such as the host's diet and living environment (Colman et al., Reference Colman, Toolson and Takacsvesbach2012; Engel and Moran, Reference Engel and Moran2013; Huang and Zhang, Reference Huang and Zhang2013). Overall, the microbiota plays an important role in an insect's life activity, providing the host with essential nutrients and protection from predators, parasites and pathogens (Tsuchida et al., Reference Tsuchida, Koga, Horikawa, Tsunoda, Maoka, Matsumoto, Simon and Fukatsu2010) and affecting reproduction (Zhang et al., Reference Zhang, Zhang, Xie, Zhao and Hong2015). Indeed, an increasing number of studies are focusing on the use of sequencing technology to analyse the functions and development of microbial communities associated with termites, silkworms and other insects (Su et al., Reference Su, Yang, Huang, Su, Li, Wang, Wang, Kang, Xu and Song2016; Sun et al., Reference Sun, Lu, Zhang, Kumar, Liu, Gong, Zhu, Zhu, Liang and Kuang2016; Chen et al., Reference Chen, Lu and Shao2017; Wang et al., Reference Wang, Wu, Chen and Yan2017). However, the effect of the microbiota on host insects remains incompletely understood.

Ectropis obliqua and E. grisescens are primary defoliators in tea plantations due to their wide distribution and destructive nature (Jiang et al., Reference Jiang, Liu, Xue, Tang, Xiao and Han2014; Zhang et al., Reference Zhang, Yuan, Zhang, Yin, Tang, Guo, Fu and Xiao2014). These moths infest thousands of hectares of tea per year, severely reducing the growth and impacting tea production in the following year (Jiang et al., Reference Jiang, Liu, Xue, Tang, Xiao and Han2014; Zhang et al., Reference Zhang, Yuan, Yin, Fu, Tang and Xiao2016a). Ectropis obliqua and E. grisescens were named in 1894 and 1930, respectively, but they have always been treated as the same species in tea garden management in China because they have similar morphology and are difficult to be distinguished (Jiang et al., Reference Jiang, Liu, Xue, Tang, Xiao and Han2014). After the two species were reacquainted in 2014, differences in morphology, reproductive capacity and virus susceptibility have been reported (Jiang et al., Reference Jiang, Liu, Xue, Tang, Xiao and Han2014; Mao et al., Reference Mao, Fu, Liang, Gui, Bai and Xiao2017; Bai et al., Reference Bai, Wang and Xiao2018a). In particular, the technique of DNA barcoding can accurately distinguish them according to the genetic distance of approximately 3.7% based on COI sequences (Jiang et al., Reference Jiang, Liu, Xue, Tang, Xiao and Han2014). Correspondingly, the distribution of the two species has become clearer, with E. obliqua being distributed in China, Japan and the Korean Peninsula and E. grisescens only in China (Wehrli, Reference Wehrli and Seitz1945; Sato, Reference Sato1984; Kim et al., Reference Kim, Beljaev, Oh and Park2001). In Zhejiang Province, in eastern China, E. grisescens is more widespread than E. obliqua, though they are both also found in some areas (Bai et al., Reference Bai, Tang, Yin, Wang and Xiao2018b). Moreover, morphological and phylogenetic evidence supports that E. obliqua is closely related to E. grisescens. Intriguingly, these sibling species can mate but produce infertile hybrids (Xi et al., Reference Xi, Yin, Tang and Xiao2014). Indeed, the hybrid F1 generation showed hatching, survival to adult stage and per cent of normal adult rates that were much lower than those with intra-species mating. Furthermore, a self-cross of F1 generation adults produced either infertile eggs or no eggs (Xi et al., Reference Xi, Yin, Tang and Xiao2014; Zhang et al., Reference Zhang, Yuan, Zhang, Yin, Tang, Guo, Fu and Xiao2014). Reproductive interference also exists between these sibling species (Zhang et al., Reference Zhang, Yuan, Yin, Fu, Tang and Xiao2016a). As these phenomena differ from those resulting from common reproductive isolation, whereby different species cannot mate and breed, we suggest that these sibling species constitute a suitable model pair for exploring reproductive isolation.

Previous studies have shown some microbiota organisms can manipulate host reproduction and even cause reproductive isolation (Philipp and Nancy, Reference Philipp and Nancy A2013; Zhang et al., Reference Zhang, Yuan, Yin, Fu, Tang and Xiao2016a, Reference Zhang, Chen, Yang, Qiao and Hong2016b). Moreover, we previously found that F1 hybrids of E. obliqua and E. grisescens showed the characteristics including unbalanced sex ratio, lower hatchability of eggs, desynchronized development of larvae and infertility that resembled cytoplasmic incompatibility which was caused by some microbiota (Bourtzis et al., Reference Bourtzis, Nirgianaki, Markakis and Savakis1996; Zhang et al., Reference Zhang, Yuan, Zhang, Yin, Tang, Guo, Fu and Xiao2014; Wang et al., Reference Wang, Bai, Liu, Li, Zhan and Xiao2019). Thus, we sought to ascertain the microbiota involved in the reproductive isolation of these sibling species. In this study, we analysed and compared differences in E. grisescens and E. obliqua microbiotal composition and found that an obvious difference in the presence of Wolbachia may be a factor influencing their reproductive isolation.

Materials and methods

Collection and preparation of samples

Ectropis obliqua larvae were collected from Yuhang (Hangzhou City, Zhejiang Province) and E. grisescens from Xinchang (Shaoxin City, Zhejiang Province). At least 200 larvae were collected in each location. The collected larvae were reared in a phytotron (temperature 24–26°C, humidity 50–70%, photoperiod L14:D10). The larvae were fed fresh leaves of the tea cultivar Yingshuang for successive three generations. Male and female individuals were separated at the pupa stage. Two days after eclosion, adult moths were randomly collected for the analysis of bacterial communities. In addition, samples from different geographical populations were collected to evaluate the rate of Wolbachia infection without rearing in the phytotron. Sampling localities of tea geometrid can be seen in fig. 1.

Figure 1. Sampling localities of tea geometrid. ■represent samples used for the detection of Wolbachia infection rate,●represent samples used for analysing bacterial communities. The abbreviation of different geographical population as follows: XC, Xinchang; YH, Yuhang; LY, Liyang; LX, Langxi; NC, Nanchang; ES, Enshi; GY, Guiyang; GY, Guiyang.

DNA extraction

Wings were removed, and other tissues were washed with sterilized water and ground for 2 min. The tissue homogenate was used for metagenomic DNA extraction using the DNeasy Blood and Tissue kit (Qiagen Co. Inc., Germany) according to the manufacturer's instruction. The quality of the extracted DNA was assessed by electrophoresis on a 1% (w/v) agarose gel. The concentration of DNA extracted was measured using a Nanodrop 2000, and the DNA samples were stored at −20°C for experiments.

Sample identification

Identification of E. obliqua and E. grisescens was confirmed by sequence analysis of the mitochondrial cytochrome oxidase I gene (COI) (Jiang et al., Reference Jiang, Liu, Xue, Tang, Xiao and Han2014). A fragment of the COI gene was amplified using the forward primer LepF1 5′-ATTCAACCAATCATAAAGATATTGG-3′ and the reverse primer Enh_LepR1 5′-CTCCWCCAGCAGGATCAAAA-3′ (Jiang et al., Reference Jiang, Liu, Xue, Tang, Xiao and Han2014). PCR using 2x Master Mix (TSINGKE Bio Inc., Hang zhou City, Zhe jiang, China) in a total reaction volume of 50 μl was performed using a Veriti 96 Well Thermal Cycler (Applied Biosystems, Foster City, CA, USA), as follows: an initial denaturation step of 95°C for 2 min, 5 cycles of 95°C for 30 s, 46°C for 1 min, and 72°C for 30 s, 35 cycles of 95°C for 30 s, 51°C for 1 min, and 72°C for 30 s and a final extension at 72°C for 10 min. Sequencing of PCR products was performed using an ABI377 genetic analyser. Sequences were assembled and edited with SeqMan 7.1.0. and aligned with CLUSTAL 1.83. The sequence of E. obliqua COI gene (accession number KJ704358), which was obtained from GenBank, was used as a control to calculate genetic distance based on Kimura-2-parameter model (100 bootstrap replicates) and build a cluster analysis tree using a maximum likelihood approach implemented in MEGA 5.05. Compared to the control sample (KJ704358), genetic distances of ~0–2.5 and 3.2–4.0%, respectively, were identified for E. obliqua and E. grisescens (Jiang et al., Reference Jiang, Liu, Xue, Tang, Xiao and Han2014).

PCR amplification of microbial 16S rDNA genes

The V3-V4 region of 16S rDNA was amplified using the forward primer 341F 5′-CCTACGGGNGGCWGCAG-3′ and the reverse primer 805R 5′-GACTACHVGGGTATCTAATCC-3′ (Sinclair et al., Reference Sinclair, Osman, Bertilsson and Eiler2015). PCR reactions were carried out with Phusion® High-Fidelity PCR Master Mix (Thermo Scientific, Waltham City, MA, USA), and the conditions of PCR amplification are as follows: pre-amplification was 94°C for 3 min, 5 cycles of 94°C for 30 s, 45°C for 20 s, and 65°C for 30 s, followed by 20 cycles of 94°C for 20 s, 55°C for 20 s, and 72°C for 30 s and a final extension at 72°C for 5 min. PCR products were examined on a 2% agarose gel. Only samples with a clear band between 400 and 450 bp were chosen for further experiments.

Sequencing of 16S rDNA gene amplicons

Sequence libraries that included 20 individuals were generated using TruSeq® DNA PCR-free Sample Preparation Kit (Illumina) according to the manufacturer's instruction. Library quality was assessed using a Qubit@ 2.0 Fluorometer (Thermo Scientific) and Agilent Bioanalyzer 2100 system (Agilent). The libraries were sequenced using the Illumina Miseq platform by Zhejiang Tianke High Technology Development Co. Ltd. (Zhejiang, China), and 300 bp paired-end (PE) reads were generated.

Detection of the Wolbachia infection rate

To determine whether the samples were infected with Wolbachia, the wsp gene was amplified from genomic DNA (Gong and Shen, Reference Gong and Shen2002; Laura et al., Reference Laura, Julie, Keith, Seth, Sarah, Choudhury, Hayashi, Maiden, Tettelin and Werren2006). The forward primer wsp_F1 5′-GTCCAATARSTGATGARGAAAC-3′ and the reverse primer wsp_R1 5′-CYGCACCAAYAGYRCTRTAAA-3′ were used (Laura et al., Reference Laura, Julie, Keith, Seth, Sarah, Choudhury, Hayashi, Maiden, Tettelin and Werren2006), and amplification was as follows: denaturation at 95°C for 3 min, 35 cycles of 95°C for 1 min, 59°C for 1 min, and 72°C for 90 s and a final extension at 72°C for 10 min. PCR products were detected by 1% agarose gel electrophoresis.

Data analysis

PE reads were merged using FLASH, and quality filtering of spliced sequences (raw tags) was performed under specific conditions to obtain high-quality clean tags according to QIIME. To detect and remove chimeric sequences, the tags were compared with reference sequences obtained from the Gold database using the UCHIME algorithm. Sequence analysis was performed using Uparse software. Sequences with ≥97% similarity were assigned to the same operational taxonomic unit (OTU). Representative sequence for each OTU was screened for further annotation.

Taxonomic assignment was achieved using the SILVA reference database (http://www.arb-silva.de/) with a threshold of 90%. The α diversity was applied when evaluating the complexity of species diversity for a sample using six indices: observed species, Chao1, Shannon, Simpson, ACE, Good's coverage. All indices were calculated using QIIME (Version 1.9.1). The β diversity analysis was applied to evaluate the differences in species complexity among the different samples, and principal coordinate analysis (PCoA) was performed based on the matrices of pairwise distances among all the microbiota. Heatmap and hierarchical cluster were built based on the relative abundance of the top 15 genera identified in the bacterial communities of samples by using pheatmap package in R program. The highly relative abundances of microbiota phyla and genera were visualized using ggplot2 package (version 3.0.0) in R program. Statistical analyses were performed using SPSS 17.0 (IBM). One-way ANOVA was followed by Tukey test for means comparison of α diversity. The level of significance was set at P < 0.05.

Result

Species verification

A total of 20 individuals were chosen for bacterial community analysis. All samples from the Yuhang population were identified as E. obliqua and numbered O1–10 (group O); all samples from the Xinchang population were identified as E. grisescens and numbered G1–10 (group G) (fig. 2; table S1).

Figure 2. The maximum likelihood (ML) tree of samples used in bacterial community analysis based on 516 bp gene segment of cytochrome oxidase I (COI) sequences. Kimura-2-parameter model was used with bootstrap percentages shown on the clades. KJ704358 (E. obliqua) was the control sample downloaded from GenBank.

Sequencing data and sequence read diversity analysis

A total of 752,452 raw PE 16S rDNA reads were generated from these 20 samples. After removal of low-quality reads, 658,249 (~75.5%) valid reads were obtained. The length of each read was between 404 and 426 bp, with an average of 417.2 bp. Q20 values for all samples were >98%. All reads clustered into 1492 OTUs (3% distance, average neighbour clustering), covering ten phyla, 40 classes, 79 orders, 118 families, 198 genera and 125 species.

Shannon and Simpson indices were used to evaluate bacterial diversity, and Chao1 and Ace indices were employed to estimate the total number of species in the samples (Sun et al., Reference Sun, Lu, Zhang, Kumar, Liu, Gong, Zhu, Zhu, Liang and Kuang2016); Good's coverage was applied for sequencing results. Significantly higher values of the Simpson index were found for E. grisescens compared to E. obliqua, whereas E. obliqua displayed significantly higher Ace and Chao1 index values (table 1). Despite a lack of a significant difference for the Shannon index between E. grisescens and E. obliqua, higher bacterial community diversity was found for E. grisescens. Overall, the high Good's coverage (both >99%) values suggest that the OTUs covered most of the bacterial communities present and that our metagenomic data were reliable.

Table 1. Estimated richness and diversity indices for the bacterial communities

a Significantly different compared to group O by Tukey test (P < 0.05); means ± SE for α diversity indices.

To compare similarity and dissimilarity between all samples, PCoA and hierarchical clustering analysis were performed. The points in fig. 3 represent samples in the PCoA plot, and the distance of each point indicates the similarity of different samples. PCoA separated the samples into two clusters, with 75.19 and 17.80% of the total variation being explained by the PCo1 and PCo2 axes, respectively. With the exception of sample O2, which was closer to group G, samples of the same species clustered together. In addition, hierarchical clustering analysis separated the samples into two clades according to species (fig. 4). Overall, the results suggest that the bacterial communities in these two species differed and that the major contribution of the difference was PCo1.

Figure 3. Principal coordinate analysis of microbiota in 20 samples based on OTUs. Each point corresponds to a sample. Red represents E. grisescens, and yellow represents E. obliqua. PCo1 and PCo2 are shown with the percentage variation explained for each axis.

Figure 4. Hierarchical clustering analysis of 20 samples based on the relative abundance of the top 15 microbiota genera identified in sibling species of tea geometrid moths.

The 16S rDNA V3-V4 region was amplified to compare the differences of the microbiota of these sibling species of tea geometrid moths. A total of 286,700 valid reads and 1043 OTUs were obtained from ten of E. obliqua samples, comprising ten phyla, 38 classes, 75 orders, 111 families, 179 genera and 118 species. Among these ten phyla (fig. 5), Firmicutes (52.80%), Proteobacteria (24.52%) and Cyanobacteria (14.05%) were highly abundant. At the genus level, 14.48% reads were not identifiable, and the remaining reads belong to the bacteria of 179 genera. The predominant genera (>1%) were Melissococcus (29.14%), Staphylococcus (23.05%), Enterobacter (14.48%), Sphingomonas (2.19%), Corynebacterium (2.30%), Methylobacterium (2.13%), Brevibacterium (1.90%) and Paracoccus (1.08%).

Figure 5. Relative abundances of microbiota phyla in sibling species of tea geometrid moths. Columns of different colour represent the abundance of the top ten microbiota. Others represent the sum abundance of those microbiota not among the top ten.

In total, 371,549 valid reads and 449 OTUs were obtained from the sequencing data for E. grisescens, covering seven phyla, 19 classes, 34 orders, 58 families, 75 genera and 40 species. Compared to E. obliqua, fewer microbiota organisms were identified in E. grisescens at all classification levels, and the composition of abundant taxa varied in these two species. The bacteria found in E. grisescens belong to seven phyla (fig. 5), with Proteobacteria (79.13%), Actinobacteria (14.06%) and Firmicutes (5.13%) being the most abundant. Comparatively, the abundances of Firmicutes and Cyanobacteria were significantly greater in E. obliqua than in E. grisescens, whereas the abundances of Proteobacteria and Actinobacteria were higher in E. grisescens (fig. 5).

At the genus level, 99.60% of the reads were identified and classified into 75 taxa. Most bacteria were found belonging to 14 genera (>1%): Wolbachia (28.97%), Enterobacter (24.16%), Pseudomonas (14.82%), Arthrobacter (7.74%), Melissococcus (5.10%), Brevibacterium (3.38%), Corynebacterium (2.19%), Acinetobacter (1.97%), Raoultella (1.94%), Sphingomonas (1.66%), Ochrobactrum (1.53%), Stenotrophomonas (1.36%), Serratia (1.34%) and Sphingobacterium (1.29%). When comparing the number of genera, 56 were shared by E. grisescens and E. obliqua, and 123 and 19 genera were unique to E. obliqua and E. grisescens, respectively. Wolbachia, Enterobacter and Pseudomonas were predominant genera in E. grisescens, the most predominant microbiota genera of E. obliqua were Melissococcus, Staphylococcus and Enterobacter, while Wolbachia (0.02%) were rare in E. obliqua (fig. 6; table 2).

Figure 6. Relative abundances of dominant microbiota genera in sibling species of tea geometrid moths. Columns of different colour represent dominant genera (relative abundance >1%).

Table 2. Wolbachia richness of 20 samples was tested using16S rDNA by Illumina Miseq platform

Detection of Wolbachia in sibling species of tea geometrid moths

We screened for four microbiota (Wolbachia, Cardinium, Spiroplasma and Rickettsia), which have been shown to influence the reproduction (Zhang et al., Reference Zhang, Chen, Yang, Qiao and Hong2016b). The results showed that only Wolbachia was found in both species. Thus, we evaluated the richness of Wolbachia in all samples used for bacterial community analysis and found it to be significantly different between the sibling species of tea geometrid moths. Specifically, the average richness of Wolbachia was 28.97% in E. grisescens, whereas it was dramatically lower in E. obliqua (0.02%). Wolbachia was not detected in female E. obliqua samples (O1–O5), but were detected in 60% of male samples (O6–O10). The richness of Wolbachia ranged from 0.03 to 0.15% in three male E. obliqua samples. In E. grisescens, infection rates varied among samples, and no significant difference between female and male moths was found (table 2).

Furthermore, we detected the infection rate of Wolbachia for samples from eight different geographical populations by amplifying wsp gene. A total of 86 samples were randomly selected for the identification of species using the CO1 gene, which were deposited in GenBank (Supplementary material table S2). The samples from Yuhang (Zhejiang) and Liyang (Jiangsu) were identified as E. obliqua and those from Xinchang (Zhejiang), Guiyang (Guizhou), Nanchang (Jiangxi), Yingde (Guangdong) and Enshi (Hubei) as E. grisescens. Additionally, samples from Langxi (Anhui) were identified as the two species (ten samples of E. obliqua and six samples of E. grisescens). The intra-specific genetic distances between those individuals were 0–0.2%, while the inter-specific genetic distances were 3.4–3.8% (Supplementary material table S3). The results of Wolbachia detection showed a Wolbachia infection rate of 0 and 100% for E. obliqua and E. grisescens, respectively (figs S1–S5). In addition, we also detected the infection rate of Wolbachia for 20 samples used for bacterial community analysis by wsp gene marker. The result showed Wolbachia were not detected in the samples with low Wolbachia infection rates (such as O6, O9 and O10) (fig. S6).

Discussion

The sibling species of tea geometrid moths E. obliqua and E. grisescens both feed on tea leaves. In our study, we controlled the rearing conditions to eliminate the influence of food and environment to explore microbiotal differences in these species. The results showed higher microbiotal diversity for E. grisescens than E. obliqua, which may offer clues for understanding why E. grisescens has a wider distribution and greater adaptability than does E. obliqua. In general, predominant microbiota differed at the genus level between these sibling species. The predominant microbiota were Melissococcus, Staphylococcus and Enterobacter in E. obliqua but Wolbachia, Enterobacter and Pseudomonas in E. grisescens. Regarding microbiota species related to reproduction, Wolbachia abundance was significantly different between these sibling species.

Wolbachia is Gram-negative bacterium first found in the oophoron of Culex pipiens (Hedges et al., Reference Hedges, Brownlie, O'Neill and Johnson2008). Wolbachia is mainly harboured in the cytoplasm of a host germ cell, with two transmission routes: common maternal vertical transfer to progeny (Hoffmann et al., Reference Hoffmann, Turelli and Harshman1990) and less common horizontal transfer among different hosts, widely broadening the host range (Huigens et al., Reference Huigens, Luck, Klaassen, Maas and Stouthamer2000; Ahmed et al., Reference Ahmed, Breinholt and Kawahara2016). Previous studies have reported the presence of Wolbachia in nematode species and many arthropods, with widespread infection in insecta (Hilgenboecker et al., Reference Hilgenboecker, Hammerstein, Schlattmann, Telschow and Werren2010). Indeed, Wolbachia has garnered intense interest because of its ability to alter the biology of its host, especially with regard to reproduction. This bacterium can manipulate insect-host reproduction in various ways including parthenogenesis (PI), feminization, male killing (MK) and CI (Lus, Reference Lus1947; Terry et al., Reference Terry, Dunn and Smith1997; Zhang et al., Reference Zhang, Zhang, Xie, Zhao and Hong2015; Lindsey et al., Reference Lindsey, Werren, Richards and Stouthamer2016). To date, PI has been found in mites, hymenopterans and thrips (Arakaki et al., Reference Arakaki, Miyoshi and Noda2001; Werren et al., Reference Werren, Baldo and Clark2008). Generally, they have a specific sex-determination system where unfertilized eggs develop into haploid males while fertilized eggs develop into diploid females (Weeks and Breeuwer, Reference Weeks and Breeuwer2001). Wolbachia can induce PI, whereby females develop without fertilization (Lindsey et al., Reference Lindsey, Werren, Richards and Stouthamer2016). In MK, male individuals are killed during embryonic development, which is induced by multiple factors, and this process has been reported in more than 20 insects (Hurst et al., Reference Hurst, Hammarton, Bandi, Majerus, Bertrand and Majerus1997), though with Wolbachia as a known cause in only Adalia bipunctata and Acraea encedon (Jiggins et al., Reference Jiggins, Hurst and Majerus2010). Among all reproductive impacts, CI is the most typical and conspicuous (Zhang et al., Reference Zhang, Zhang, Xie, Zhao and Hong2015). In the simplest form, CI can be described as embryonic mortality that occurs when uninfected females mate with Wolbachia-infected males (Bourtzis et al., Reference Bourtzis, Nirgianaki, Markakis and Savakis1996). Most CI embryos exhibit defects in paternal chromosome condensation, resulting in paternal ‘diffused chromatin’ that cannot be normally distributed to the zygote during metaphase I (Uyen et al., Reference Uyen, Kurt, Werren and William2006). Previous studies have reported CI in Acari, Coleoptera, Diptera, Hemiptera, Hymenoptera, Isopoda, Lepidoptera and Orthoptera (Bourtzis et al., Reference Bourtzis, Nirgianaki, Markakis and Savakis1996; Werren et al., Reference Werren, Baldo and Clark2008; Chevalier, Reference Chevalier2012; Pinto et al., Reference Pinto, Kirsty, Simon, Zakaria, Sutton, Bonsall, Julian and Sinkins2013; Zhang et al., Reference Zhang, Zhang, Xie, Zhao and Hong2015).

In our study, E. grisescens was found to be infected with Wolbachia, but E. obliqua showed little infection by this genus, which is in line with the CI requirement of mating between uninfected and infected individuals. Recent research has indicated that the hatching rate of the filial generation was notably decreased when female E. grisescens mated with male E. obliqua and that it was even lower when female E. obliqua mated with male E. grisescens (Xi et al., Reference Xi, Yin, Tang and Xiao2014; Zhang et al., Reference Zhang, Yuan, Zhang, Yin, Tang, Guo, Fu and Xiao2014). Overall, our results are in accord with CI and suggest that Wolbachia might be an important factor causing reproductive isolation between these species.

Generally, the fundamental rule of distinguishing species is reproductive isolation which may result from prezygotic or postzygotic barriers (Dobzhansky, Reference Dobzhansky1970). In our study, the kind of phenomenon, can mate but produce sterile offspring between the two tea loopers, belongs to postzygotic isolation (Haldane, Reference Haldane1922). The postzygotic isolation is a rare phenomenon relative to prezygotic in nature and exists in those species which have a close genetic relationship such as Spodoptera frugiperda (fall armyworm). Spodoptera frugiperda is polyphagous and a major agricultural pest in the North and South American continent and Caribbean (Gouin et al., Reference Gouin, Bretaudeau, Nam, Gimenez, Aury, Duvic, Hilliou, Durand, Montagné, Darboux, Kuwar, Chertemps, Siaussat, Bretschneider, Moné, Ahn, Hänniger, Grenet, Neunemann, Maumus, Luyten, Labadie, Xu, Koutroumpa, Escoubas, Llopis, Maïbèche-Coisne, Salasc, Tomar, Anderson, Khan, Dumas, Orsucci, Guy, Belser, Alberti, Noel, Couloux, Mercier, Nidelet, Dubois, Liu, Boulogne, Mirabeau, Gof, Gordon, Oakeshott, Consoli, Volkof, Fescemyer, Marden, Luthe, Herrero, Heckel, Wincker, Kergoat, Amselem, Quesneville, Groot, Jacquin-Joly, Nègre, Lemaitre, Legeai, d'Alençon and Fournier2017). It consists of two sympatric host-plant strains, C strain feeding mostly on maize cotton and sorghum and R strain mostly associated with rice and various pasture grasses (Gouin et al., Reference Gouin, Bretaudeau, Nam, Gimenez, Aury, Duvic, Hilliou, Durand, Montagné, Darboux, Kuwar, Chertemps, Siaussat, Bretschneider, Moné, Ahn, Hänniger, Grenet, Neunemann, Maumus, Luyten, Labadie, Xu, Koutroumpa, Escoubas, Llopis, Maïbèche-Coisne, Salasc, Tomar, Anderson, Khan, Dumas, Orsucci, Guy, Belser, Alberti, Noel, Couloux, Mercier, Nidelet, Dubois, Liu, Boulogne, Mirabeau, Gof, Gordon, Oakeshott, Consoli, Volkof, Fescemyer, Marden, Luthe, Herrero, Heckel, Wincker, Kergoat, Amselem, Quesneville, Groot, Jacquin-Joly, Nègre, Lemaitre, Legeai, d'Alençon and Fournier2017). These two strains are morphologically indistinguishable but estimated to be 2.09% on average in the COI gene (Kergoat et al., Reference Kergoat, Prowell, Le Ru, Mitchell, Dumas, Clamens, Condamine and Silvain2012). Compared to genetic distances of other species, Dumas et al. proposed that C and R strains were pairs of differentiated species (sister-species) in the Spodoptera genus (Dumas et al., Reference Dumas, Legeai, Lemaitre, Scaon, Orsucci, Labadie, Gimenez, Clamens, Henri, Vavre, Aury, Fournier, Kergoat and d'Alencon2015a, Reference Dumas, Barbut, Le Ru, Silvain, Clamens, d'Alencon and Kergoat2015b). More important, C and R strains also showed the phenomenon of postzygotic isolation (Groot et al., Reference Groot, Marr, Heckel and Schöfl2016). Though bacterial endosymbionts can cause genetic incompatibilities in hybrids, Dumas et al. investigated the presence of Wolbachia and several other bacteria in both C and R strains of S. frugiperda, but did not detect any of them, accordingly, eliminated the factor that bacteria manipulate their host reproduction (Dumas et al., Reference Dumas, Legeai, Lemaitre, Scaon, Orsucci, Labadie, Gimenez, Clamens, Henri, Vavre, Aury, Fournier, Kergoat and d'Alencon2015a). However, in our study, E. obliqua and E. grisescens have identical dietary habits and differential bacterial endosymbiont in Wolbachia. Therefore, this pair of insects constitute suitable material for research that Wolbachia mediating host reproduction isolation.

The results of this study reveal the diversity of microbiota taxa between sibling species of tea geometrid moths. In particular, the notable difference in Wolbachia may be the major factor influencing the reproductive isolation of these sibling species. Overall, Wolbachia is an important microbiota genus manipulating insect-host reproduction in various ways. In addition, more functions of Wolbachia can be explored in these model sibling species of tea geometrid moths, such as Wolbachia interaction with pheromones and EoNPV. Nonetheless, further research is required to explore the mechanism by which Wolbachia is involved in reproductive isolation between sibling species of tea geometrid moths.

Supplementary material

The supplementary material for this article can be found at https://doi.org/10.1017/S0007485320000164.

Acknowledgments

We thank Dr Zhishuo Wang (University of Edinburgh, Edinburgh), Dr Liang Sun and Dr Xin Li (Tea Research Institute, Chinese Academy of Agricultural Sciences, Hangzhou) for providing language and writing assistance.

Financial support

This work was supported by the National Key R&D Program of China (2017YFE0107500), the National Natural Science Foundation of China (31700613), Special Project on Basic Scientific Research (2013FY113200) and the Science and Technology Innovation Project of the Chinese Academy of Agricultural Sciences (CAAS-ASTIP-2016-TRICAAS).

Conflict of interest

The authors declare that they have no conflict of interest.

Ethical standards

This article does not contain any studies with human participants or animals performed by any of the authors.

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Figure 0

Figure 1. Sampling localities of tea geometrid. ■represent samples used for the detection of Wolbachia infection rate,●represent samples used for analysing bacterial communities. The abbreviation of different geographical population as follows: XC, Xinchang; YH, Yuhang; LY, Liyang; LX, Langxi; NC, Nanchang; ES, Enshi; GY, Guiyang; GY, Guiyang.

Figure 1

Figure 2. The maximum likelihood (ML) tree of samples used in bacterial community analysis based on 516 bp gene segment of cytochrome oxidase I (COI) sequences. Kimura-2-parameter model was used with bootstrap percentages shown on the clades. KJ704358 (E. obliqua) was the control sample downloaded from GenBank.

Figure 2

Table 1. Estimated richness and diversity indices for the bacterial communities

Figure 3

Figure 3. Principal coordinate analysis of microbiota in 20 samples based on OTUs. Each point corresponds to a sample. Red represents E. grisescens, and yellow represents E. obliqua. PCo1 and PCo2 are shown with the percentage variation explained for each axis.

Figure 4

Figure 4. Hierarchical clustering analysis of 20 samples based on the relative abundance of the top 15 microbiota genera identified in sibling species of tea geometrid moths.

Figure 5

Figure 5. Relative abundances of microbiota phyla in sibling species of tea geometrid moths. Columns of different colour represent the abundance of the top ten microbiota. Others represent the sum abundance of those microbiota not among the top ten.

Figure 6

Figure 6. Relative abundances of dominant microbiota genera in sibling species of tea geometrid moths. Columns of different colour represent dominant genera (relative abundance >1%).

Figure 7

Table 2. Wolbachia richness of 20 samples was tested using16S rDNA by Illumina Miseq platform

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