Introduction
Cockroaches are hemimetabolous insects with three major life stages (ootheca, nymph and adult), which have existed for 30 million years and more than 4600 extant have been described (Guzman and Vilcinskas, Reference Guzman and Vilcinskas2020). Like other cockroaches, Periplaneta americana is a resilient insect and it can endure prolonged starvation and dehydration, allowing it to survive for nearly 1 month without food or water (Taylor and Freckleton, Reference Taylor and Freckleton1969). Furthermore, P. americana has been found with strong reproductive ability; it can reproduce by parthenogenesis and some female cockroaches can store sperm after copulation event to allow eggs to be fertilised and laid without the presence of a male (Wharton and Wharton, Reference Wharton and Wharton1957). These biological characteristics contribute to the fitness and success of P. americana at different life stages in the face of environmental challenges. However, the reason why P. americana has such strong environmental adaptive and reproductive abilities is not entirely clear.
Gut microbiota is one of the important components of the intestinal system of host, and the microecology constituted by gut bacteria can actively interact with the hosts which may affect the host's physiological functions and behaviours such as growth, development, reproduction, etc. (Nicholson et al., Reference Nicholson, Holmes, Kinross, Burcelin, Gibson, Jia and Pettersson2012; Cani et al., Reference Cani, Van Hul, Lefort, Depommier, Rastelli and Everard2019; Agus et al., Reference Agus, Clément and Sokol2021). Recently, the intricate relationship of gut microbiota with insect host has been catching great interests and gut microbiota has also been found to establish mutualistic symbiotic associations with insects (Feldhaar, Reference Feldhaar2011). Previous studies have revealed that gut microbiota played crucial roles in the life cycles of insect and it may be attributed to nutrient provisioning and stress response (Chouaia et al., Reference Chouaia, Goda, Mazza, Alali, Florian, Gionechetti, Callegari, Gonella, Magoga, Fusi, Crotti, Daffonchio, Alma, Paoli, Roversi, Marianelli and Montagna2019; Jahnes et al., Reference Jahnes, Herrmann and Sabree2019). For instance, the symbionts such as Enterobacter cloacae, Providencia stuartii and Lysinibacillus sphaericus play a role in nutrition supplement and mediate the normal development of dung beetle (Onthophagus taurus and Onthophagus gazella) (Estes et al., Reference Estes, Hearn, Snell-Rood, Feindler, Feeser, Abebe, Dunning Hotopp and Moczek2013; Schwab et al., Reference Schwab, Riggs, Newton and Moczek2016). Moreover, gut symbiont can enhance insecticide resistance in the oriental fruit fly (Bactrocera dorsalis) which may improve the survival and development of host (Cheng et al., Reference Cheng, Guo, Riegler, Xi, Liang and Xu2017). Therefore, we assumed the gut microbiota might be an important regulator for the strong vitality and environmental adaptability of P. americana at different life stages.
Herein, this study has profiled the gut bacterial communities at ootheca, nymph and adult stage of P. americana by 16S rRNA high-throughput sequencing. Then multivariate statistical analysis was conducted to compare the diversity and composition of the bacterial communities across different life stages, and the metabolic functions have been predicted by PICRUst based on the KEGG database. This study was the first to report the alterations in gut microbiota across different life stags of P. americana, and the results were expected to elucidate the roles of gut microbiota in the strong vitality and adaptability throughout different life stages of P. americana.
Materials and method
Sample collection and DNA extraction
The P. americana insects in this study were provided by Guangdong Provincial Center for Disease Control and Prevention, and reared under laboratory conditions. A total of 15 samples of P. americana across different life stages were used in this study and there were five samples from each life stage. The morphology and size of ootheca, nymph and adult of P. americana used in this study were shown in fig. S1. The nymph and adult samples were paralysed at 4°C for 15 min and washed alternatively with water and 75% ethanol three times before dissection. The intestinal tracts were then quickly removed and washed carefully in sterile 1× PBS. For ootheca samples, the contents of ootheca were removed quickly after washing alternatively with water and 75% ethanol for three times. The samples were transferred to a sterile mortar into liquid N2 and ground with a sterile pestle for 30 min. All samples were stored at −80°C until DNA extraction.
The DNA extraction of the samples was carried out by the PowerSoil DNA Isolation Kit (ANBIOSCI TECH LTD, Shenzhen, China) according to the instructions provided by the manufacturer and the DNA extraction methodologies of soil or root samples (Rodrigues et al., Reference Rodrigues, Pellizari, Mueller, Baek, Jesus, Paula, Mirza, Hamaoui, Tsai, Feigl, Tiedje, Bohannan and Nüsslein2013).
PCR amplification, library preparation and high-throughput sequencing
The V3–V4 region of the bacterial 16S rRNA gene was amplified by PCR using the 338F/806R primer set (338F: 5'-ACTCCTACGGGAGGCAGCA-3', 806R: 5'-GGACTACHVGGGTWTCTAAT-3') (Yu et al., Reference Yu, Lee, Kim and Hwang2005; Walters et al., Reference Walters, Hyde, Berg-Lyons, Ackermann, Humphrey, Parada, Gilbert, Jansson, Caporaso, Fuhrman, Apprill and Knight2016). The PCR was performed in a total volume of 50 μl containing 0.2 μl Q5 high-fidelity DNA polymerase, 10 μl high GC enhancer, 10 μl buffer, 1 μl dNTP, 1.5 μl of each primer (10 μM), 40–60 ng of DNA template and deionised ultrapure water to 50 μl. The conditions of the PCR were as follows: denaturation step at 95°C for 5 min; 15 cycles at 95°C for 1 min, 50°C for 1 min and 72°C for 1 min; and a final extension step at 72°C for 7 min. The PCR products were verified by 1.8% agarose gel electrophoresis and the samples with a bright main band of approximately 450 bp were mixed in equidensity ratios. Then, the mixture of PCR products was purified by GeneJETGel Extraction Kit (Thermo Fisher Scientific, Waltham, MA, USA) and quantified with Qubit 2.0 Fluorometer (Thermo Fisher). The resultant products were sent for sequencing using the Illumina HiSeq 2500 platform (Illumina, Inc., San Diego, CA, USA) and the 16S rRNA libraries were generated at Biomarker Bioinformatics Technology, Co., Ltd. (Beijing, China). The raw sequences obtained in this study have been submitted to the NCBI Sequence Read Archive database under the SRA accession number PRJNA517316 (BioSample accession numbers SAMN10826798 to SAMN10826812).
Bioinformatic analysis
The overlapping regions between the paired-end were merged into longer single sequences using FLASH (v1.2.7) (Magoč and Salzberg, Reference Magoč and Salzberg2011), and the raw reads were quality filtered under the specific filtering conditions (Bokulich et al., Reference Bokulich, Subramanian, Faith, Gevers, Gordon, Knight, Mills and Caporaso2013) to obtain high-quality clean tags on the basis of the quality-control program suite QIIME (v1.8.0) (Caporaso et al., Reference Caporaso, Kuczynski, Stombaugh, Bittinger, Bushman, Costello, Fierer, Peña, Goodrich, Gordon, Huttley, Kelley, Knights, Koenig, Ley, Lozupone, McDonald, Muegge, Pirrung, Reeder, Sevinsky, Turnbaugh, Walters, Widmann, Yatsunenko, Zaneveld and Knight2010). Sequences that were less than 200 bp in length or that contained homopolymers longer than 8 bp were removed. The chimeric sequences were detected by comparing tags with the references database (RDP Gold database) and removed using the UCHIME algorithm. The effective sequences were obtained and used in the final analysis.
Operational taxonomic units (OTUs) were clustered on the basis of 97% similarity sequence identity using the clustering program UCLUST (v1.2.22) (Edgar, Reference Edgar2010). Then OTUs were taxonomically classified to different levels of phylum, class, order, family, genus and species by the Ribosomal Database Program (RDP) classifier. Alpha-diversity analyses (i.e. observed species, ACE, Chao 1, Shannon and Simpson indices) were calculated by QIIME (v.1.8.0) used for richness and diversity indices of the gut bacterial community in each sample. The partial least squares-discriminant analysis (PLS-DA) was conducted by MetaboAnalyst 5.0 based on the normalised data, and the R 2 and Q 2 of the model were 0.99 and 0.89, respectively. The functional gene content in the gut microbiome was predicted by Phylogenetic Investigation of Communities by Reconstruction of Unobserved States (PICRUSt2).
Statistical analysis
Alpha-diversity indices were presented as the means ± SEM. The differences in alpha-diversity indices and relative abundances between groups at the phyla and genus levels were calculated using Kruskal–Wallis H-test. The relationships between bacterial relative abundance and KEGG orthologue groups across different life stages were conducted by Spearman's correlation analysis. All of the statistical analyses were conducted by IBM SPSS Statistics for Windows, Version 22.0 (IBM Corp, Armonk, USA). The p-value <0.05 was considered statistically significant. The figures in this study were drawn by GraphPad Prism 9.0 and the Charticulator online software.
Results
Quality of sequencing data
To better understand the role of gut microbiota in host physiological functions, development and behaviours, it is necessary to increase the quality of sequencing and metagenomic analysis to obtain more information about the composition and function of gut microbiota. In this study, the gut microbiota from P. americana across different life stages were analysed by 16S rRNA sequencing with variation in V3–V4 region. A total of 3,584,855 high-quality sequences and 1599 OTUs were generated from 15 assayed samples, with an average of 238,990 reads and 1060 OTUs per sample (table S1). The percentage of OTU in samples were estimated by the Good's coverage index and the average bacterial coverage was 0.99 ± 0.00019, suggesting the obtained data could adequately cover the gut flora of P. americana. Moreover, the rarefaction curves and rank-abundance curves tended to approach the saturation plateau (fig. 1), which indicated that more data would only produce a small number of new OTUs and the sequencing data volume in this study was sufficient.
Figure 1. The rarefaction curves (a) and rank-abundance curves (b) of sequencing data from each P. americana sample across different life stages. A01 to A05 represented ootheca samples, B01 to B05 represented nymph samples and C01 to C05 represented adult samples.
Diversity and richness of gut microbiota in different life stages
The alterations in gut microbiota profile across development of life stages of P. americana have been evaluated by using Venn analysis and PLS-DA based on the OTU number. A total of 1169 OTUs were shared across three life stages of and there are 8, 17 and 31 unique OTUs in ootheca, nymph and adult samples, respectively (fig. 2a). PLS-DA model showed a clear distinction among each life stage with good predictive ability (R 2 = 0.99, Q 2 = 0.89, permutation p < 0.01), indicating the bacterial community in each life stage was different (fig. 2b). In addition, the diversity of gut microbiota was determined by the Simpson and Shannon indices, and the richness of gut microbiota was evaluated by ACE and Chao1 indices. As shown in fig. 2c, the Shannon, ACE and Chao1 indices of nymph and adult samples were significantly higher than that in ootheca, while Simpson indices were significantly lower.
Figure 2. Diversity and richness of gut microbiota across different life stages of P. americana. (a) Venn diagram based on OTUs in different life stages. (b) PLS-DA score plot of each sample across different life stages (R 2 = 0.99, Q 2 = 0.89, permutation p < 0.01). (c) Species diversity (Simpson and Shannon) and richness (ACE and Chao1) indices of each sample across different life stages. *p < 0.05, **p < 0.01 represented significant differences.
Taxonomic view of gut microbiota across life stages
To further investigate the differences of gut microbiota structure and composition among each life stage of P. americana, all sequences obtained in this study were classified and identified based on the lowest taxonomic level at phylum and genus levels. Twenty-eight phyla and 353 genera were identified and the shared and unique phyla and genera in each life stage were shown in fig. S2. The phyla and genera with relative abundance more than 1% in ootheca, nymph and adult samples were elected and the relative abundance was shown in fig. 3. As shown in the results, Bacteroidetes and Firmicutes showed high relative abundances in ootheca (90.87 ± 2.39% and 7.89 ± 2.31%), nymph (37.95 ± 1.99% and 32.28 ± 2.63%) and adult (53.76 ± 3.23% and 23.03 ± 2.29%) samples, which were the main components of bacterial communities of P. americana in different life stages. For genus level, the results showed that Blattabacterium was the dominant genus in bacterial community of ootheca samples with high relative abundance of 88.18 ± 3.22%. Moreover, Christensenellaceae and Ruminococcaceae showed high relative abundance in nymph samples (6.85 ± 0.66% and 3.84 ± 0.22%) compared to adult (2.13 ± 0.26% and 1.86 ± 0.23%).
Figure 3. Taxonomic composition of the top 20 most abundant bacterial phyla (a) and genera (b) in the gut microbiota of different life stages of P. americana.
Functional prediction of gut microbiota across life stages
To better understand how the gut microbiota carry on various metabolic functions beneficial to the host in different development stages, the metagenomes (based on the KEGG database) of the samples in each life stage of P. americana were predicted by PICRUSt2 analysis (fig. S3). The PLS-DA based on the obtained KEGG functional profile was performed and the model showed pronounced separations among each life stage with good permutation (R 2 = 0.77, Q 2 = 0.48, empirical p < 0.05), which suggested that the functional composition of the samples differed among each life stage (fig. S4). A total of 35 KEGG pathways (relative abundance in any life stage samples >1%) were identified at level 3 and its relative abundances in each sample were shown in fig. 4a. The results showed that the metabolic categories, including biosynthesis of amino acids, ribosome and carbon metabolism, exhibited a high frequency in ootheca, nymph and adult samples. However, there are several unique metabolic categories with high relative abundance in ootheca samples such as phenylalanine, tyrosine and tryptophan biosynthesis, glycine, serine and threonine metabolism and citrate cycle (TCA cycle). Furthermore, the specific KEGG orthologue groups related to physiological functions were compared among life stages by Kruskal–Wallis H-test based on the relative abundances (fig. 4b). The results showed that the relative abundances of amino acid metabolism, nucleotide metabolism and translation were significantly higher in ootheca samples than in nymph, while carbohydrate metabolism, membrane transport and signal transduction were significantly lower.
Figure 4. Functional metagenomes prediction of each life sage based on KEGG database. (a) Relative abundance of the metabolic categories at level 3 in each sample at different life stages. (b) Comparison of the specific KEGG orthologue groups related to physiological functions among different life stages. *p < 0.05 and **p < 0.01 represented significant difference.
Discussion
Gut microbiota, one of the most important components in the gastrointestinal tract, has been reported to play critical roles in the physiological functions and society behaviours of P. americana (Ayayee et al., Reference Ayayee, Ondrejech, Keeney and Muñoz-Garcia2018; Lee et al., Reference Lee, Kim, Yi, Lee, Lee, Moon, Yong and Yong2020). Although several researches have revealed the compositions and structures of intestinal bacterial communities in P. americana, its alterations across ootheca, nymph and adult life stages and the functions of gut microbiota in different life stages were still unclear. The results in our study revealed the diversity and richness of bacterial communities in nymph and adult were significantly higher than in ootheca of P. americana. It has been revealed that the gut microbiota was not constant across the developments of life stages in most of insects (Aharon et al., Reference Aharon, Pasternak, Ben Yosef, Behar, Lauzon, Yuval and Jurkevitch2013; Zhukova et al., Reference Zhukova, Sapountzis, Schiøtt and Boomsma2017), and the diversity and richness of bacterial community in nymph and adult are mostly higher than ootheca on account of the physiological needs of the host (Vacchini et al., Reference Vacchini, Gonella, Crotti, Prosdocimi, Mazzetto, Chouaia, Callegari, Mapelli, Mandrioli, Alma and Daffonchio2017; Malacrinò et al., Reference Malacrinò, Campolo, Medina and Palmeri2018).
Similar to the findings of previous studies, the taxonomic analysis in this work showed Bacteroidetes and Firmicutes were the dominant phyla in bacterial communities of P. americana across each life stage, which have been considered to contribute to diet processing in cockroach (Bertino-Grimaldi et al., Reference Bertino-Grimaldi, Medeiros, Vieira, Cardoso, Turque, Silveira, Albano, Bressan-Nascimento, Garcia, de Souza, Martins and Machado2013; Vera-Ponce de León et al., Reference Vera-Ponce de León, Jahnes, Duan, Camuy-Vélez and Sabree2020). At the genus level, Blattabacterium showed high relative abundance in ootheca while Christensenellaceae and Ruminococcaceae were one of the genera with high relative abundance of bacterial communities in nymph and adult. Previous studies found that the bacteria belonging to the genera Christensenellaceae and Ruminococcaceae that are closely associated with the host degrade and metabolise cellulose (Flint et al., Reference Flint, Scott, Duncan, Louis and Forano2012; Liu et al., Reference Liu, Zhang, Zhou, Zhang, Yan, Wang, Long, Xie, Wang, Huang and Zhou2013), suggesting that the nymph of P. americana has stronger digestive ability than adult, and thus better nutrient absorption. Both the taxonomic composition at phylum and genus levels revealed that the bacterial communities in nymph and adult samples were more complex and varied than in ootheca. Shaping of bacterial community structure may be influenced by environmental and host behavioural factors, and its composition could reflect at least in part the host evolution in that the microbiota may derive from the microbiota of a common ancestor (Berlanga, Reference Berlanga2015). Therefore, the results in this study revealed that gut microbiota might change along the developments of life stages of P. americana to better meet the physiological needs.
Then metagenomes (based on the KEGG database) of the samples in each life stage of P. americana were predicted by PICRUSt2 analysis to further investigate how gut microbiota carry on various metabolic functions beneficial to the host in different development stages. The results showed that the metabolic categories closely associated to the basic physiological function of host, including biosynthesis of amino acids, ribosome and carbon metabolism, exhibited a high frequency in ootheca, nymph and adult of P. americana. Several unique metabolic categories, including phenylalanine, tryptophan and threonine, are the amino acids which have been revealed to play a critical role in insect ootheca production and viability and broadly in development and reproduction (Arya et al., Reference Arya, Toltesi, Eng, Garg, Merritt and Rajpurohit2021), and showed high relative abundance in ootheca samples. In addition, it was also found that two-component system and amino sugar and nucleotide sugar metabolism only exhibited high relative abundance in nymph samples. As the metabolic categories belonged to signal transduction and carbohydrate metabolism, two-component system and amino sugar and nucleotide sugar metabolism related to bacteria have been found to be involved in perceptions of environment, reaction to the changing conditions, adaptions to various stress factors and organ size development of host (Stock et al., Reference Stock, Robinson and Goudreau2000; Heermann and Fuchs, Reference Heermann and Fuchs2008; Zhang et al., Reference Zhang, Blessing, Wu, Liu, Li, Qin and Li2017). Spearman's analysis results also showed that the alterations in relative abundance of gut bacteria at genus levels were significantly correlated with the compositions of metabolic orthologue across different life stages of P. americana (fig. S5). It was suggested that the functions of bacterial communities in ootheca might have more influence on the basic life activities of the host than improved production and viability of ootheca (Noma, Reference Noma2005; Sabree et al., Reference Sabree, Kambhampati and Moran2009). On the other hand, high relative levels of carbohydrate metabolism, membrane transport and signal transduction in nymph and adult samples might be more associated to the society activities, reproduction and development of host (Zhang et al., Reference Zhang, Zhang, Yang, Zhang and Liu2018).
In conclusion, this study has profiled the gut microbiota of P. americana across different life stages by 16S rRNA high-throughput sequencing and it was found that the diversity and structure of gut microbiota were significantly varied across different life stages. In addition, the metagenomes analysis based on KEGG database showed the functions of gut microbiota in ootheca might have more influence on the basic life activities while that in nymph and adult might be more associated to the society activities, reproduction and development. These results suggested that the gut microbiota might be altered across different life stages of P. americana and it might contribute to the specific physiological functions via mediating the metabolic capabilities, which provided a novel sight to better understand the strong resilient and environmental adaptability throughout different life stages of P. americana.
Supplementary material
The supplementary material for this article can be found at https://doi.org/10.1017/S0007485323000469.
Data availability statement
The data that support the findings of this study are available in NCBI at https://www.ncbi.nlm.nih.gov/bioproject/PRJNA517316.
Acknowledgements
This work was funded by the Public Welfare Research and Capacity Building Project of Guangdong Province (No. 2016A030303059 and No. 2017A020211008). The Key Projects of Basic Research and Applied Basic Research of Guangdong Province Normal University (No. 2018KZDXM041).
Competing interests
None.
Ethical standards
The article does not contain any studies with human participants or animals performed by any of the authors.
