The gut microbial community structure of adult Thrips tabaci collected from 10 different agro-climatically diverse locations of India was characterized by using the Illumina MiSeq platform to amplify the V3 region of the 16S rRNA gene of bacteria present in the sampled insects. Analyses were performed to study the bacterial communities associated with Thrips tabaci in India. The complete bacterial metagenome of T. tabaci was comprised of 1662 OTUs of which 62.25% belong to known and 37.7% of unidentified/unknown bacteria. These OTUs constituted 21 bacterial phyla of 276 identified genera. Phylum Proteobacteria was predominant, followed by Actinobacteria, Firmicutes, Bacteroidetes and Cyanobacteria. Additionally, the occurrence of the reproductive endosymbiont, Wolbachia was detected at two locations (0.56%) of the total known OTUs. There is high variation in diversity and species richness among the different locations. Alpha-diversity metrics indicated the higher gut bacterial diversity at Bangalore and lowest at Rahuri whereas higher bacterial species richness at T. tabaci samples from Imphal and lowest at Jhalawar. Beta diversity analyses comparing bacterial communities between the samples showed distinct differences in bacterial community composition of T. tabaci samples from different locations. This paper also constitutes the first record of detailed bacterial communities associated with T. tabaci. The location-wise variation in microbial metagenome profile of T. tabaci suggests that bacterial diversity might be governed by its population genetic structure, environment and habitat.
Citation: Gawande SJ, Anandhan S, Ingle A, Roylawar P, Khandagale K, Gawai T, et al. (2019) Microbiome profiling of the onion thrips, Thrips tabaci Lindeman (Thysanoptera: Thripidae). PLoS ONE 14(9): e0223281. https://doi.org/10.1371/journal.pone.0223281
Editor: Ulrich Melcher, Oklahoma State University, UNITED STATES
Received: May 27, 2019; Accepted: September 17, 2019; Published: September 30, 2019
Copyright: © 2019 Gawande et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Data Availability: All relevant data are within the paper and its Supporting Information files.
Funding: This work was supported by HORTDOGRSIL201800400084, INDIAN COUNCIL OF AGRICULTURAL RESEARCH, https://icar.org.in/, to SJG. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Competing interests: The authors have declared that no competing interests exist.
Bacterial communities in insects play an important role in their growth, development, immunological, physiological and morphological functioning. The majority of insects are believed to harbour heritable bacterial symbionts  that can be pathogenic, mutualist, or commensal, with some required for survival while others are not. Across Insecta, microorganisms have been reported to positively influence many functions, including the production of essential amino acids from nutrient poor diets , protection against toxic agents [3–5], aide in the production of honey , protection against parasitoids , virus transmission , insecticide resistance , degradation of phytotoxins and pesticides . Conversely, some are reported to negatively impact insects by causing sterility and distorting sex ratios [11,12]. Despite their influence on important metabolic processes in the host, they have not been accurately profiled due to the difficulty in isolating and culturing many of the symbionts. Identification of symbionts has been improved with the availability of next generation sequencing technology, which, bypasses the need of isolating and culturing, can detect microbes present in very low amounts, and facilitates the study of the microbial community in its natural habitat with accurate taxonomic identification and their relative abundances . Characterizing the diversity of symbionts is an important first step towards understanding their importance in the life history of organisms.
There is a growing area of interest regarding the presence and influence of heritable endosymbionts on the biology and ecology of economically important insects, and on the phenotypes that influence pest status. Several studies on endosymbionts have targeted pest species that damage crops by feeding on plants and transmitting plant pathogens such as aphids , whiteflies , and thrips . The studies have identified endosymbionts that influence fitness , virus transmission , host plant preferences , protection from biological control agents , and insecticide resistance . Endosymbionts are also of interest as targets for future pest control strategies that could be achieved by disturbing the essential symbionts of insect pests and symbionts which contribute to their pest status .
Onion thrips, Thrips tabaci Lindeman (Thysanoptera: Thripidae), is a globally important polyphagous insect pest. It has been collected from approximately 300 plant species that includes economically important crops such as leek, garlic, tobacco, cabbage, pea, melon, lettuce, potato, tomato, carnation, and cotton [20,21], and causes more than $1 billion losses worldwide to onion alone . In addition to damaging crops through direct feeding, T. tabaci is a vector of the Orthotospoviruses Iris yellow spot virus (IYSV) and Tomato spotted wilt virus (TSWV) [23,24]. Onion thrips exhibits three different reproductive modes (thelytoky, arrhenotoky and deuterotoky) , host-associated lineages, variation in virus (TSWV) vector competence , heteroplasmy of mtCOI haplotypes  and develop resistance to insecticides quickly. Variation in these phenotypes may be due to selection on standing genetic variation but could be influenced by their microbiome. Insect bacterial communities may also influence their reproduction [28,29] and virus transmission efficiency of thrips .
To date, limited information is available regarding the endosymbiont profiles of this species; there is one study that examined one population using culturing methods  or only one bacteria species was examined25. The objectives of this study were to identify bacterial microbiota present in T. tabaci from ten distinct locations of India using the Illumina MiSeq platform to sequence the V3 region of 16s rRNA, and examine patterns of bacterial diversity within and among these locations.
Materials and methods
Thrips tabaci has not been notified under any act or laws and rules thereof of the Government of India as an endangered or threatened species restricting or regulating its collection and observation. Therefore, permits were not required for collecting T. tabaci for the present study.
Adult T. tabaci were collected from 10 different states in India during rabi season (December-June) of the year 2013–2014. The states sampled encompassed different climatic zones in India, including temperate, tropical, and subtropical zones of the country (Fig 1). Approximately 500 thrips were collected from each state (50 thrips from each field, 10 fields per location), and were sampled within 1–2 days from each other. Adult thrips were dislodged from onion leaves with a fine brush into a 2 ml Eppendorf tubes containing 95% ethanol. To make certain offspring from different adults were collected, a distance of 1.5 m was kept between sampled plants. Voucher specimens are located at plant protection section, ICAR-Directorate of Onion and Garlic Research, Rajgurunagar, Pune.
Adult T. tabaci were surface sterilized by rinsing them with 100% ethanol. Genomic DNA was extracted from pool of 500 adult thrips from each location using a standard phenol-chloroform and ethanol precipitation method .
Bacterial 16S rRNA gene amplification, library preparation and sequencing
16S rRNA gene sequencing was performed at SciGenom Labs Private Limited (Cochin, India) on an Illumina MiSeq 2 x 151 platform (Illumina, Inc., San Diego, CA, USA). Base quality score distributions, average base content per read and GC distribution in the reads were used as quality check parameters for sequences obtained from the sequencer (Illumina MiSeq).
Bioinformatics and statistical analysis
To identify bacteria present in the samples sequence data needed to be filtered for quality, aligned into contigs, and blasted against existing bacterial sequence databases. An average of 361,241 paired end sequences with a length of 151bp were obtained from sequencing 10 samples (minimum 218,538; maximum: 499,241). Gut microbiome analysis was performed with QIIME2 2017.9 framework . Raw sequences were quality filtered and denoised followed by chimera filtering with DADA2  to obtain amplicon sequence variants (ASV). Low abundant ASVs with a total frequency less than ten were filtered out of the dataset. Taxonomy assignment was performed with a pre-trained Silva 132 99% OTUs based naïve Bayes classifier and confidence threshold of 0.7 using q2-feature-classifier plugin . ASVs matching with chloroplast, mitochondria and eukaryotic sequences were removed from the database for downstream analysis. A taxonomic summary table was generated for each level of taxonomy for phylotype abundance.
Sequence alignment using MAFFT  was performed for all ASVs and used for the construction of phylogeny with fasttree2 . Alpha rarefaction plotting was performed with a minimum and a maximum depth of 100 and 10000 respectively to identify an ideal sampling depth for further analysis. Three alpha diversity indices namely, Shannon, chao1, and simpson_e at ideal sampling depth have been estimated. The similarity of bacterial communities between samples (beta diversity) was quantified using a metric based on phylotype abundances. The distance matrix was generated using weighted UniFrac approach , and a jackknife test with 100 iterations was performed to construct a consensus UPGMA (Unweighted Pair Group Method with Arithmetic Mean) tree. Principal Coordinates Analysis (PCoA) was performed to generate a 3D PCoA plot in EMPeror .
ANCOM compares the log ratio of the abundance of each taxon to the abundance of all the remaining taxa one at a time . ANCOM (ANalysis of Composition Of Microbiomes) was performed to identify taxa with differential abundance among sample groups. ANCOM is now incorporated into the QIIME suite for metagenome analyses. For ANCOM analysis samples were grouped into four climatic zones according to Köppen classification viz; (Monatne (MON): Shrinagar; Humid subtropical (HST): Hisar, Imphal, Jabalpur, Samastipur; Tropical wet and dry (TWD): Pune, Rahuri, Chiplima and Semi-arid (SA): Bangalore and Jhalawar.
The Illumina MiSeq sequencing of the V3 region of 16S rRNA gene of onion thrips from ten different locations yielded 218,538–499,241 raw reads per location. Nearly 80% of the total reads had Phred scores greater than 30 (>Q30; error-probability > = 0.001) indicating good quality of data. GC content of the reads ranged from 40 to 60% and after filtering contig length (~150bp). After quality filtering 39,976–140,603 reads per sample remained. Pre-processed reads from all samples were pooled for a total of 962,166 reads, and from them, a total of 1662 OTUs were identified (Table 1).
Microbiome profile of T. tabaci
A total of 21 phyla, which constitute 62.25% of the total 16S rRNA gene data set, were detected from T. tabaci in this study (S1 File). The majority of bacterial contigs were of unknown origin (33%) while 4.7% were unknown bacteria. The contigs that do not have any alignment against the taxonomic database were categorized as “Unassigned”. From the identifiable bacterial sequences, the majority belonged to phylum Proteobacteria, followed by Firmicutes, Actinobacteria, Bacteroidetes and Cyanobacteria (Fig 2, Fig 3). Across all locations, these five phyla comprised more than 60% of the total microbiome and more than 96% of identified microbiome of T. tabaci.
At the bacterial class level, the Proteobacteria were comprised of 26 Gamma-, 7.1% Alpha-proteobacteria. In Firmicutes, classes Bacilli and Clostridia represented 14.1% and 10%, respectively. In the phylum Actinobacteria, classes Actinobacteria and Coriobacteria represented 16.8% and 3.5%, respectively. Class Bacteroidia of phylum Bacteroidetes constituted 10.6% of total identified microbiome and classes Oxyphotobacteria and Melainabacteria of phylum Cyanobacteria represented 3.4%, and 0.2%, respectively. At the genus level, a total 276 genera were identified from the present study. The highest number of genera are from phylum Proteobacteria (69) followed by Firmicutes (61), Actinobacteria (44), Bacteroidetes (29) and Chloroflexi (13). Among them, the genus Streptococcus (phylum Firmicutes) was most prevalent and comprised 8.03% of contigs, followed by Pseudomonas (5.4%) (phylum Proteobacteria), Rosenbergiella (4.5%) (phylum Proteobacteria), Alistipes (2.7%) (phylum Bacteroidetes) and Saccharopolyspora (2.05%) (phylum Actinobacteria). In addition, reproductive endosymbiont Wolbachia was recorded at 0.56% of the total OTUs. A few plant endophytes were also identified from gut of onion thrips in the present study such as Actinomyces, Microbacterium, and Burkholderia at very low levels.
Microbiome diversity of T. tabaci at different location
Alpha-diversity indices (Shannon, Simpson-e) describe the diversity of the microbial community at each sampling location and showed that bacterial diversity is higher in Bangalore, followed by Jabalpur and that the lowest bacterial diversity is observed in Rahuri. Another alpha diversity index (Chao1) describes the species richness at each sampling location. Among ten locations, bacterial richness is found to be highest in Bangalore and lowest in the Jhalawar (Table 2). Beta diversity considers the variations in bacterial community composition for different environments. Bacterial diversity among locations was assessed using both the weighted and unweighted UniFrac approach. UniFrac distances are based on the fraction of branch length of the 16S rRNA phylogenetic tree shared between two communities. The UPGMA tree and PCoA plots were constructed using the weighted UniFrac distance matrix. Locations were clustered based on the bacterial community structure. From PCoA plot it has been seen that there is high diversity among the bacterial communities of T. tabaci from different geographical location (Fig 4). PC-1 and PC-2 explain 61.87% and 22.1% cumulative variance in the microbiome of the T. tabaci, respectively. ANCOM analyses reveals two genera in Montane zone Chryseobacterium and Exiguobacterium found to be higher in Shrinagar location (S2 File, S3 File).
UPGMA tree (A) and PCoA plot (B) showing relationships between the gut bacterial communities from T. tabaci collected from 10 different geographic locations and based on β-diversity metrics calculated using UniFrac.
Microorganisms exhibit a variety of interactions with their hosts and most of the time these interactions are beneficial to the insect . Despite being an economically important pest, the information on insect-microbe interactions of T. tabaci is very limited. Recently, NGS has become the method of choice for insect microbiome analyses due to the ability to detect both culturable and non-culturable bacteria. The present study constitutes the first detailed examination of bacterial communities in T. tabaci using sequencing methods. In this study phyla Proteobacteria, Actinobacteria, Firmicutes and Bacteroidetes together constituted more than 90% of the total T. tabaci identified microbiome. These phyla are also reported to be the predominant in the microbiomes of other thrips species [16,41,42], several insects [43,44,45], and amphibians .
Phylum Proteobacteria was predominant at four of the ten reported locations. Proteobacteria plays an important role in carbohydrate degradation in Wood Borer, Saperda vestita , vitamins synthesis  and detoxification of pesticides fruit fly Bactrocera dorsalis [49,10]. The phylum Actinobacteria, was abundant at two locations and is reported to increase metabolic versatility and the ability to exploit the wide range of nutritional resources e.g. polysaccharides like cellulose  and hemicelluloses in termites  and production of secondary metabolites with antibiotic properties . The third most prevalent phylum was Firmicutes, which predominated at three locations. Bacteria in Firmicutes were also abundant in guts of termites and honeybees [53,54]. Several studies in insects and animals have shown that Firmicutes increased the ability to metabolize food resources to increase energy conversion from diet , and assist in the digestion of cellulose and hemicelluloses . Bacteroidetes were the fourth predominant phylum in present16S rDNA data set. The members of this phyla are known for their role in the production of enzymes such as glucanase, mannanase and xylanase that aid in complex carbohydrate metabolism [57,58]. Phylum Cyanobacteria was prevalent in one location, and these bacteria are associated with high levels of protein, vitamins, and microelements. They are known to release toxins during their life that lead to concentration dependent, and species-specific negative effects on animal feeders . These five phyla were also found to be predominant in the microbiome of the other thrips species Scirtothrips dorsalis and Hoplothrips carpathicus [16,42].
We detected the genus Wolbachia, in two out of ten locations. Wolbachia infects over 40% of all arthropods  and is known to manipulate sex determination mechanisms and sex ratio by cytoplasmic factors, cytoplasmic incompatibility [61,62]. This is the first report of Wolbachia in T. tabaci. Studies have looked presence of Wolbachia in different thrips species but did not find it in T. tabaci [25,29]. Wolbachia has been reported in other thrips species such as Echinothrips americanus, Gynaikothrips ficorum, Suocerathrips linguis , Thrips palmi  and Hoplothrips carpathicus  but their role in T. tabaci is unclear.
Few plant origin endophytes such as Actinomyces, Microbacterium, and Burkholderia were recorded in the microbiome of T. tabaci. Theses endophytes might have been acquired by the insect during feeding on plants. Their occurrence in insects gut has been well documented in previous studies [64,65].
Streptococcus, Saccharopolyspora, Phormidium, Pseudomonas, Prevotella, Serratia, Erwinia and Propionibacterium were the most predominant genera in the microbiome of T. tabaci, and were also reported to be predominant in the microbiome of several other thrips species [16,66,67,30,68,42].
This study marks the first attempt to document the endosymbiont diversity associated with T. tabaci in India. Diversity indices showed that T. tabaci from Bangalore has the highest bacterial diversity and Imphal has the highest species richness. Further UPGMA and PCoA analyses showed bacterial communities structured by location. This spatial variation in the microbiome T. tabaci might be due to geographical location, climatic conditions and host phylogeny. In several insects, variation in the microbiome with respect to climatic conditions, the geography of habitat, and phylogeny of the insect have been documented [69,42,14].
This paper described the microbiome of T. tabaci collected from the different geographical locations of India using NGS approach. Findings of the present study increased understanding of microbiome of T. tabaci as well as its variation with respect to geography and climatic conditions. Though it is first report of its kind in T. tabaci, for more in depth study of T. tabaci microbiome needs to be done at different developmental stages for better understanding of its role in development and growth of T. tabaci.
The authors are grateful to the Indian Council of Agricultural Research (ICAR) for funding.
- 1. Duron O, Hurst GD. Arthropods and inherited bacteria: from counting the symbionts to understanding how symbionts count. Bmc Biology. 2013 Dec;11(1):45.
- 2. Hansen AK, Moran NA. Aphid genome expression reveals host–symbiont cooperation in the production of amino acids. Proceedings of the National Academy of Sciences. 2011 Feb 15;108(7):2849–54.
- 3. Douglas AE. The ecology of symbiotic micro-organisms. In Advances in Ecological Research 1995 Jan 1 (Vol. 26, pp. 69–103). Academic Press.
- 4. Dillon RJ, Vennard CT, Charnley AK. Pheromones: exploitation of gut bacteria in the locust. Nature. 2000 Feb;403(6772):851.
- 5. Houk EA, Griffiths GW. Intracellular symbiotes of the Homoptera. Annual review of entomology. 1980 Jan;25(1):161–87.
- 6. Lee FJ, Miller KI, McKinlay JB, Newton IL. Differential carbohydrate utilization and organic acid production by honey bee symbionts. FEMS microbiology ecology. 2018 Jun 6;94(8):fiy113.
- 7. Vorburger C. Symbiont-conferred resistance to parasitoids in aphids–challenges for biological control. Biological Control. 2018 Jan 1;116:17–26.
- 8. Su Q, Pan H, Liu B, Chu D, Xie W, Wu Q, Wang S, Xu B, Zhang Y. Insect symbiont facilitates vector acquisition, retention, and transmission of plant virus. Scientific Reports. 2013 Mar 4;3:1367.
- 9. Xia X, Sun B, Gurr GM, Vasseur L, Xue M, You M. Gut microbiota mediate insecticide resistance in the Diamondback moth, Plutella xylostella (L.). Frontiers in microbiology. 2018 Jan 23;9:25. pmid:29410659
- 10. Itoh H, Tago K, Hayatsu M, Kikuchi Y. Detoxifying symbiosis: microbe-mediated detoxification of phytotoxins and pesticides in insects. Natural product reports. 2018;35(5):434–54. pmid:29644346
- 11. Breeuwer JA. Wolbachia and cytoplasmic incompatibility in the spider mites Tetranychus urticae and T. turkestani. Heredity. 1997 Jul;79(1):41.
- 12. Vala F, Weeks A, Claessen D, Breeuwer JA, Sabelis MW. Within‐and between‐population variation for Wolbachia‐induced reproductive incompatibility in a haplodiploid mite. Evolution. 2002 Jul;56(7):1331–9. pmid:12206235
- 13. Cao Y., Fanning S., Proos S., Jordan K. & Srikumar S. A Review on the Applications of Next Generation Sequencing Technologies as Applied to Food-Related Microbiome Studies. Front. Microbiol. 8, 1829; pmid:29033905
- 14. Zhao Y, Zhang S, Luo JY, Wang CY, Lv LM, Cui JJ. Bacterial communities of the cotton aphid Aphis gossypii associated with Bt cotton in northern China. Scientific reports. 2016 Apr 15;6:22958. pmid:27079679
- 15. Lv ZH, Wei XY, Tao YL, Chu D. Differential susceptibility of whitefly-associated bacteria to antibiotic as revealed by metagenomics analysis. Infection, Genetics and Evolution. 2018 Sep 1;63:24–9. pmid:29702243
- 16. Dickey AM, Trease AJ, Jara-Cavieres A, Kumar V, Christenson MK, Potluri LP, Morgan JK, Shatters RG Jr, Mckenzie CL, Davis PH, Osborne LS. Estimating bacterial diversity in Scirtothrips dorsalis (Thysanoptera: Thripidae) via next generation sequencing. The Florida entomologist. 2014 Jun;97(2):362. pmid:25382863
- 17. Himler AG, Adachi-Hagimori T, Bergen JE, Kozuch A, Kelly SE, Tabashnik BE, Chiel E, Duckworth VE, Dennehy TJ, Zchori-Fein E, Hunter MS. Rapid spread of a bacterial symbiont in an invasive whitefly is driven by fitness benefits and female bias. science. 2011 Apr 8;332(6026):254–6. pmid:21474763
- 18. Ferrari J, Scarborough CL, Godfray HC. Genetic variation in the effect of a facultative symbiont on host-plant use by pea aphids. Oecologia. 2007 Aug 1;153(2):323–9. pmid:17415589
- 19. Douglas AE. Symbiotic microorganisms: untapped resources for insect pest control. TRENDS in Biotechnology. 2007 Aug 1;25(8):338–42. pmid:17576018
- 20. Lewis T. Thrips as crop pests. Cab International; 1997.
- 21. Diaz-Montano J, Fuchs M, Nault BA, Fail J, Shelton AM. Onion thrips (Thysanoptera: Thripidae): a global pest of increasing concern in onion. Journal of Economic Entomology. 2011 Feb 1;104(1):1–3. pmid:21404832
- 22. Gent DH, du Toit LJ, Fichtner SF, Mohan SK, Pappu HR, Schwartz HF. Iris yellow spot virus: an emerging threat to onion bulb and seed production. Plant Disease. 2006 Dec;90(12):1468–80. pmid:30780964
- 23. Rotenberg D, Jacobson AL, Schneweis DJ, Whitfield AE. Thrips transmission of tospoviruses. Current Opinion in Virology. 2015 Dec 1;15:80–9. pmid:26340723
- 24. Riley DG, Joseph SV, Srinivasan R, Diffie S. Thrips vectors of tospoviruses. Journal of Integrated Pest Management. 2011 Apr 1;2(1):I1–0.
- 25. Nault BA, Shelton AM, Gangloff-Kaufmann JL, Clark ME, Werren JL, Cabrera-la Rosa JC, Kennedy GG. Reproductive modes in onion thrips (Thysanoptera: Thripidae) populations from New York onion fields. Environmental Entomology. 2006 Oct 1;35(5):1264–71.
- 26. Jacobson AL, Kennedy GG. Specific insect-virus interactions are responsible for variation in competency of different Thrips tabaci isolines to transmit different Tomato spotted wilt virus isolates. PLoS One. 2013 Jan 24;8(1):e54567. pmid:23358707
- 27. Gawande SJ, Anandhan S, Ingle AA, Jacobson A, Asokan R. Heteroplasmy due to coexistence of mtCOI haplotypes from different lineages of the Thrips tabaci cryptic species group. Bulletin of entomological research. 2017 Aug;107(4):534–42. pmid:28137324
- 28. Koivisto RK, Braig HR. Microorganisms and parthenogenesis. Biological Journal of the Linnean Society. 2003 May 1;79(1):43–58.
- 29. Kumm S, Moritz G. First detection of Wolbachia in arrhenotokous populations of thrips species (Thysanoptera: Thripidae and Phlaeothripidae) and its role in reproduction. Environmental Entomology. 2008 Dec 1;37(6):1422–8. pmid:19161685
- 30. De Vries EJ, Van der Wurff AW, Jacobs G, Breeuwer JA. Onion thrips, Thrips tabaci, have gut bacteria that are closely related to the symbionts of the western flower thrips, Frankliniella occidentalis. Journal of Insect Science. 2008 Jan 1;8(1):23.
- 31. Sambrook J, Fritsch EF, Maniatis T. Molecular cloning: a laboratory manual. Cold spring harbor laboratory press; 1989.
- 32. Bolyen E, Jai Ram R, Matthew RD, Nicholas AB, Christian CA, Gabriel A, et al. Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2. Nat. Biotechnol. (2019): 1.
- 33. Callahan BJ, McMurdie PJ, Rosen MJ, Han AW, Johnson AJA., Holmes SP. DADA2: high-resolution sample inference from Illumina amplicon data. Nature methods. 2016 Jul;13(7):581. pmid:27214047
- 34. Bokulich NA, Kaehler BD, Rideout JR, Dillon M, Bolyen E, Knight R, Huttley GA, Caporaso JG. Optimizing taxonomic classification of marker-gene amplicon sequences with QIIME 2’s q2-feature-classifier plugin. Microbiome. 2018 Dec;6(1):90. pmid:29773078
- 35. Katoh K, Standley DM. MAFFT multiple sequence alignment software version 7: improvements in performance and usability. Mol. Biol. Evol. 2013 Jan 16;30(4):772–80. pmid:23329690
- 36. Price MN, Dehal PS, Arkin AP. FastTree 2–approximately maximum-likelihood trees for large alignments. PloS one. 2010 Mar 10;5(3):e9490. pmid:20224823
- 37. Lozupone C, Knight R. UniFrac: a new phylogenetic method for comparing microbial communities. Appl. Environ. Microbiol. 2005 Dec 1;71(12):8228–35. pmid:16332807
- 38. Vázquez-Baeza Y, Pirrung M, Gonzalez A, Knight R. EMPeror: a tool for visualizing high-throughput microbial community data. Gigascience. 2013 Dec;2(1):16. pmid:24280061
- 39. Mandal S, Van Treuren W, White RA, Eggesbø M, Knight R, Peddada SD. Analysis of composition of microbiomes: a novel method for studying microbial composition. Microbial ecology in health and disease. 2015 Dec 1;26(1):27663.
- 40. Engel P, Moran NA. The gut microbiota of insects–diversity in structure and function. FEMS microbiology reviews. 2013 Sep 1;37(5):699–735. pmid:23692388
- 41. Powell CM, Montiel AL, Beddingfield B, Hanson JD, Bextine BR. Comparison of Bacterial Communities of Flower Thrips (Frankliniella tritici 1) and Potato Psyllid (Bactericera cockerelli 2). Southwestern Entomologist. 2015 Dec;40(4):765–74.
- 42. Kaczmarczyk A, Kucharczyk H, Kucharczyk M, Kapusta P, Sell J, Zielińska S. First insight into microbiome profile of fungivorous thrips Hoplothrips carpathicus (Insecta: Thysanoptera) at different developmental stages: molecular evidence of Wolbachia endosymbiosis. Scientific reports. 2018 Sep 26;8(1):14376 pmid:30258200
- 43. Jones RT, Sanchez LG, Fierer N. A cross-taxon analysis of insect-associated bacterial diversity. PLoS one. 2013 Apr 16;8(4):e61218. pmid:23613815
- 44. Yun JH, Roh SW, Whon TW, Jung MJ, Kim MS, Park DS, Yoon C, Nam YD, Kim YJ, Choi JH, Kim JY. Insect gut bacterial diversity determined by environmental habitat, diet, developmental stage, and phylogeny of host. Appl. Environ. Microbiol. 2014 Sep 1;80(17):5254–64. pmid:24928884
- 45. Kim JM, Choi MY, Kim JW, Lee SA, Ahn JH, Song J, Kim SH, Weon HY. Effects of diet type, developmental stage, and gut compartment in the gut bacterial communities of two Cerambycidae species (Coleoptera). Journal of Microbiology. 2017 Jan 1;55(1):21–30.
- 46. McKenzie VJ, Bowers RM, Fierer N, Knight R, Lauber CL. Co-habiting amphibian species harbor unique skin bacterial communities in wild populations. The ISME journal. 2012 Mar;6(3):588. pmid:21955991
- 47. Delalibera I Jr, Handelsman JO, Raffa KF. Contrasts in cellulolytic activities of gut microorganisms between the wood borer, Saperda vestita (Coleoptera: Cerambycidae), and the bark beetles, Ips pini and Dendroctonus frontalis (Coleoptera: Curculionidae). Environmental Entomology. 2005 Jun 1;34(3):541–7.
- 48. McCutcheon JP, Moran NA. Parallel genomic evolution and metabolic interdependence in an ancient symbiosis. Proceedings of the National Academy of Sciences. 2007 Dec 4;104(49):19392–7.
- 49. Cheng D, Guo Z, Riegler M, Xi Z, Liang G, Xu Y. Gut symbiont enhances insecticide resistance in a significant pest, the oriental fruit fly Bactrocera dorsalis (Hendel). Microbiome. 2017 Dec;5(1):13. pmid:28143582
- 50. Pasti MB, Belli ML. Cellulolytic activity of actinomycetes isolated from termites (Termitidae) gut. FEMS microbiology letters. 1985 Jan 1;26(1):107–12.
- 51. Schäfer A, Konrad R, Kuhnigk T, Kämpfer P, Hertel H, König H. Hemicellulose‐degrading bacteria and yeasts from the termite gut. Journal of Applied Bacteriology. 1996 May;80(5):471–8. pmid:9072518
- 52. Kaltenpoth M. Actinobacteria as mutualists: general healthcare for insects?. Trends in microbiology. 2009 Dec 1;17(12):529–35. pmid:19853457
- 53. Auer L, Lazuka A, Sillam-Dussès D, Miambi E, O'Donohue M, Hernandez-Raquet G. Uncovering the potential of termite gut microbiome for lignocellulose bioconversion in anaerobic batch bioreactors. Frontiers in microbiology. 2017 Dec 22;8:2623. pmid:29312279
- 54. Martinson VG, Danforth BN, Minckley RL, Rueppell O, Tingek S, Moran NA. A simple and distinctive microbiota associated with honey bees and bumble bees. Molecular Ecology. 2011 Feb;20(3):619–28. pmid:21175905
- 55. Chen B, Teh BS, Sun C, Hu S, Lu X, Boland W, Shao Y. Biodiversity and activity of the gut microbiota across the life history of the insect herbivore Spodoptera littoralis. Scientific reports. 2016 Jul 8;6:29505. pmid:27389097
- 56. Brown SD, Lamed R, Morag E, Borovok I, Shoham Y, Klingeman DM, Johnson CM, Yang Z, Land ML, Utturkar SM, Keller M. Draft genome sequences for Clostridium thermocellum wild-type strain YS and derived cellulose adhesion-defective mutant strain AD2. 2012: 3290–3291 pmid:22628515
- 57. Flint HJ, Bayer EA, Rincon MT, Lamed R, White BA. Polysaccharide utilization by gut bacteria: potential for new insights from genomic analysis. Nature Reviews Microbiology. 2008 Feb;6(2):121. pmid:18180751
- 58. Dai X, Zhu Y, Luo Y, Song L, Liu D, Liu L, Chen F, Wang M, Li J, Zeng X, Dong Z. Metagenomic insights into the fibrolytic microbiome in yak rumen. PloS one. 2012 Jul 13;7(7):e40430. pmid:22808161
- 59. Krivosheina MG. On insect feeding on cyanobacteria. Paleontological Journal. 2008 Oct 1;42(6):596–9.
- 60. Zug R, Hammerstein P. Still a host of hosts for Wolbachia: analysis of recent data suggests that 40% of terrestrial arthropod species are infected. PloS one. 2012 Jun 7;7(6):e38544. pmid:22685581
- 61. Zug R, Hammerstein P. Bad guys turned nice? A critical assessment of Wolbachia mutualisms in arthropod hosts. Biological Reviews. 2015 Feb;90(1):89–111. pmid:24618033
- 62. Beukeboom LW, Perrin N. The evolution of sex determination. Oxford University Press, USA; 2014.
- 63. Saurav GK, Daimei G, Rana VS, Popli S, Rajagopal R. Detection and Localization of Wolbachia in Thrips palmi Karny (Thysanoptera: Thripidae). Indian journal of microbiology. 2016 Jun 1;56(2):167–71. pmid:27570308
- 64. Priya NG, Ojha A, Kajla MK, Raj A, Rajagopal R. Host plant induced variation in gut bacteria of Helicoverpa armigera. PloS one. 2012 Jan 26;7(1):e30768. pmid:22292034
- 65. Lòpez-Fernàndez S, Mazzoni V, Pedrazzoli F, Pertot I, Campisano A. A phloem-feeding insect transfers bacterial endophytic communities between grapevine plants. Frontiers in microbiology. 2017 May 15;8:834. pmid:28555131
- 66. De Vries EJ, Jacobs G, Sabelis MW, Menken SB, Breeuwer JA. Diet–dependent effects of gut bacteria on their insect host: the symbiosis of Erwinia sp. and western flower thrips. Proceedings of the Royal Society of London. Series B: Biological Sciences. 2004 Oct 22;271(1553):2171–8.
- 67. Chanbusarakum L, Ullman D. Characterization of bacterial symbionts in Frankliniella occidentalis (Pergande), Western flower thrips. Journal of invertebrate pathology. 2008 Nov 1;99(3):318–25. pmid:18809409
- 68. Ranjith MT, Harish ER, Girija D, Nazeem PA. Bacterial communities associated with the gut of tomato fruit borer, Helicoverpa armigera (Hübner) (Lepidoptera: Noctuidae) based on Illumina Next-Generation Sequencing. Journal of Asia-Pacific Entomology. 2016 Jun 1;19(2):333–40.
- 69. Pan H, Li X, Ge D, Wang S, Wu Q, Xie W, Jiao X, Chu D, Liu B, Xu B, Zhang Y. Factors affecting population dynamics of maternally transmitted endosymbionts in Bemisia tabaci. PloS one. 2012 Feb 23;7(2):e30760. pmid:22383972