Skip to main content
SpringerLink
Log in

Evaluation of Sample Preservation Approaches for Better Insect Microbiome Research According to Next-Generation and Third-Generation Sequencing

  • Methods
  • Published:
Microbial Ecology Aims and scope Submit manuscript

Abstract

The microbial communities associated with insects play critical roles in many physiological functions such as digestion, nutrition, and defense. Meanwhile, with the development of sequencing technology, more and more studies begin to focus on broader biodiversity of insects and the corresponding mechanisms of insect microbial symbiosis, which need longer time collecting in the field. However, few studies have evaluated the effect of insect microbiome sample preservation approaches especially in different time durations or have assessed whether these approaches are appropriate for both next-generation sequencing (NGS) and third-generation sequencing (TGS) technologies. Here, we used Tessaratoma papillosa (Hemiptera: Tessaratomidae), an important litchi pest, as the model insect and adopted two sequencing technologies to evaluate the effect of four different preservation approaches (cetyltrimethylammonium bromide (CTAB), ethanol, air dried, and RNAlater). We found the samples treated by air dried method, which entomologists adopted for morphological observation and classical taxonomy, would get worse soon. RNAlater as the most expensive approaches for insect microbiome sample preservation did not suit for field works longer than 1 month. We recommended CTAB and ethanol as better preservatives in longer time field work for their effectiveness and low cost. Comparing with the full-length 16S rRNA gene sequenced by TGS, the V4 region of 16S rRNA gene sequenced by NGS has a lower resolution trait and may misestimate the composition of microbial communities. Our results provided recommendations for suitable preservation approaches applied to insect microbiome studies based on two sequencing technologies, which can help researchers properly preserve samples in field works.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5

Similar content being viewed by others

Data Availability

These sequence data have been submitted to the GenBank databases under accession number PRJNA676180.

References

  1. Zilber-Rosenberg I, Rosenberg E (2008) Role of microorganisms in the evolution of animals and plants: the hologenome theory of evolution. FEMS Microbiol Rev 32:723–735. https://doi.org/10.1111/j.1574-6976.2008.00123.x

    Article  CAS  PubMed  Google Scholar 

  2. Lemanceau P, Blouin M, Muller D, Moenne-Loccoz Y (2017) Let the core microbiota be functional. Trends Plant Sci 22:583–595. https://doi.org/10.1016/j.tplants.2017.04.008

    Article  CAS  PubMed  Google Scholar 

  3. Simon JC, Marchesi JR, Mougel C, Selosse MA (2019) Host–microbiota interactions: from holobiont theory to analysis. Microbiome 7:5. https://doi.org/10.1186/s40168-019-0619-4

    Article  PubMed  PubMed Central  Google Scholar 

  4. Van Borm S, Buschinger A, Boomsma JJ, Billen J (2002) Tetraponera ants have gut symbionts related to nitrogen-fixing root-nodule bacteria. P Roy Soc B-Biol Sci 269:2023–2027. https://doi.org/10.1098/rspb.2002.2101

    Article  CAS  Google Scholar 

  5. Colman DR, Toolson EC, Takacs-Vesbach CD (2012) Do diet and taxonomy influence insect gut bacterial communities? Mol Ecol 21:5124–5137. https://doi.org/10.1111/j.1365-294X.2012.05752.x

    Article  CAS  PubMed  Google Scholar 

  6. Sudakaran S, Retz F, Kikuchi Y, Kost C, Kaltenpoth M (2015) Evolutionary transition in symbiotic syndromes enabled diversification of phytophagous insects on an imbalanced diet. Isme J 9:2587–2604. https://doi.org/10.1038/ismej.2015.75

    Article  PubMed  PubMed Central  Google Scholar 

  7. Florez LV, Scherlach K, Gaube P, Ross C, Sitte E, Hermes C, Rodrigues A, Hertweck C, Kaltenpoth M (2017) Antibiotic-producing symbionts dynamically transition between plant pathogenicity and insect-defensive mutualism. Nat Commun 8:15172. https://doi.org/10.1038/ncomms15172

    Article  PubMed  PubMed Central  Google Scholar 

  8. Liu N, Li HJ, Chevrette MG, Zhang L, Cao L, Zhou HK, Zhou XG, Zhou ZH, Pope PB, Currie CR, Huang YP, Wang Q (2019) Functional metagenomics reveals abundant polysaccharide-degrading gene clusters and cellobiose utilization pathways within gut microbiota of a wood-feeding higher termite. Isme J 13:104–117. https://doi.org/10.1038/s41396-018-0255-1

    Article  CAS  PubMed  Google Scholar 

  9. Sudakaran S, Kost C, Kaltenpoth M (2017) Symbiont acquisition and replacement as a source of ecological innovation. Trends Microbiol 25:375–390. https://doi.org/10.1016/j.tim.2017.02.014

    Article  CAS  PubMed  Google Scholar 

  10. Mao M, Bennett GM (2020) Symbiont replacements reset the co-evolutionary relationship between insects and their heritable bacteria. Isme J 14:1384–1395. https://doi.org/10.1038/s41396-020-0616-4

    Article  PubMed  PubMed Central  Google Scholar 

  11. Yao ZC, Ma QK, Cai ZH, Raza MF, Bai S, Wang YC, Zhang P, Ma HQ, Zhang HY (2019) Similar shift patterns in gut bacterial and fungal communities across the life stages of Bactrocera minax larvae from two field populations. Front Microbiol 10:2262. https://doi.org/10.3389/fmicb.2019.02262

    Article  PubMed  PubMed Central  Google Scholar 

  12. Shukla SP, Plata C, Reichelt M, Steiger S, Heckel DG, Kaltenpoth M, Vilcinskas A, Vogel H (2018) Microbiome-assisted carrion preservation aids larval development in a burying beetle. P Natl Acad Sci Usa 115:11274–11279. https://doi.org/10.1073/pnas.1812808115

    Article  CAS  Google Scholar 

  13. Vogel H, Shukla SP, Engl T, Weiss B, Fischer R, Steiger S, Heckel DG, Kaltenpoth M, Vilcinskas A (2017) The digestive and defensive basis of carcass utilization by the burying beetle and its microbiota. Nat Commun 8:15186. https://doi.org/10.1038/ncomms15186

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Walters W, Hyde ER, Berg-Lyons D, Ackermann G, Humphrey G, Parada A, Gilbert JA, Jansson JK, Caporaso JG, Fuhrman JA, Apprill A, Knight R (2016) Improved bacterial 16S rRNA gene (V4 and V4–5) and fungal internal transcribed spacer marker gene primers for microbial community surveys. MSystems 1:e00009. https://doi.org/10.1128/mSystems.00009-15

    Article  PubMed  Google Scholar 

  15. Buermans HPJ, den Dunnen JT (2014) Next generation sequencing technology: advances and applications. Bba-Mol Basis Dis 1842:1932–1941. https://doi.org/10.1016/j.bbadis.2014.06.015

    Article  CAS  Google Scholar 

  16. Fuks G, Elgart M, Amir A, Zeisel A, Turnbaugh PJ, Soen Y, Shental N (2018) Combining 16S rRNA gene variable regions enables high-resolution microbial community profiling. Microbiome 6:17. https://doi.org/10.1186/s40168-017-0396-x

    Article  PubMed  PubMed Central  Google Scholar 

  17. Deutscher AT, Burke CM, Darling AE, Riegler M, Reynolds OL, Chapman TA (2018) Near full-length 16S rRNA gene next-generation sequencing revealed Asaia as a common midgut bacterium of wild and domesticated Queensland fruit fly larvae. Microbiome 6:85. https://doi.org/10.1186/s40168-018-0463-y

    Article  PubMed  PubMed Central  Google Scholar 

  18. Burke CM, Darling AE (2016) A method for high precision sequencing of near full-length 16S rRNA genes on an Illumina MiSeq. Peerj 4:e2492. https://doi.org/10.7717/peerj.2492

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. van Dijk EL, Jaszczyszyn Y, Naquin D, Thermes C (2018) The third revolution in sequencing technology. Trends Genet 34:666–681. https://doi.org/10.1016/j.tig.2018.05.008

    Article  CAS  PubMed  Google Scholar 

  20. Ameur A, Kloosterman WP, Hestand MS (2019) Single-molecule sequencing: towards clinical applications. Trends Biotechnol 37:72–85. https://doi.org/10.1016/j.tibtech.2018.07.013

    Article  CAS  PubMed  Google Scholar 

  21. Singer E, Bushnell B, Coleman-Derr D, Bowman B, Bowers RM, Levy A, Gies EA, Cheng JF, Copeland A, Klenk HP, Hallam SJ, Hugenholtz P, Tringe SG, Woyke T (2016) High-resolution phylogenetic microbial community profiling. Isme J 10:2020–2032. https://doi.org/10.1038/ismej.2015.249

    Article  PubMed  PubMed Central  Google Scholar 

  22. Crotti E, Balloi A, Hamdi C, Sansonno L, Marzorati M, Gonella E, Favia G, Cherif A, Bandi C, Alma A, Daffonchio D (2012) Microbial symbionts: a resource for the management of insect-related problems. Microb Biotechnol 5:307–317. https://doi.org/10.1111/j.1751-7915.2011.00312.x

    Article  PubMed  PubMed Central  Google Scholar 

  23. Lee WJ, Brey PT (2013) How microbiomes influence metazoan development: insights from history and Drosophila modeling of gut–microbe interactions. Annu Rev Cell Dev Bi 29:571–592. https://doi.org/10.1146/annurev-cellbio-101512-122333

    Article  CAS  Google Scholar 

  24. Raymann K, Moran NA (2018) The role of the gut microbiome in health and disease of adult honey bee workers. Curr Opin Insect Sci 2:97–104. https://doi.org/10.1016/j.cois.2018.02.012

    Article  Google Scholar 

  25. Birer C, Tysklind N, Zinger L, Duplais C (2017) Comparative analysis of DNA extraction methods to study the body surface microbiota of insects: a case study with ant cuticular bacteria. Mol Ecol Resour 17:e34–e45. https://doi.org/10.1111/1755-0998.12688

    Article  CAS  PubMed  Google Scholar 

  26. Ng SH, Stat M, Bunce M, Simmons LW (2018) The influence of diet and environment on the gut microbial community of field crickets. Evol Ecol 8:4704–4720. https://doi.org/10.1002/ece3.3977

    Article  Google Scholar 

  27. Wu GD, Lewis JD, Hoffmann C, Chen YY, Knight R, Bittinger K, Hwang J, Chen J, Berkowsky R, Nessel L, Li H, Bushman FD (2010) Sampling and pyrosequencing methods for characterizing bacterial communities in the human gut using 16S sequence tags. BMC Microbiol 10:206. https://doi.org/10.1186/1471-2180-10-206

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. Hale VL, Tan CL, Knight R, Amato KR (2015) Effect of preservation method on spider monkey (Ateles geoffroyi) fecal microbiota over 8 weeks. J Microbiol Methods 113:16–26. https://doi.org/10.1016/j.mimet.2015.03.021

    Article  PubMed  Google Scholar 

  29. Song SJ, Amir A, Metcalf JL, Amato KR, Xu ZZ, Humphrey G, Knight R (2016) Preservation methods differ in fecal microbiome stability, affecting suitability for field studies. Msystems 1:e00021–e00016. https://doi.org/10.1128/mSystems.00021-16

    Article  PubMed  PubMed Central  Google Scholar 

  30. Gorzelak MA, Gill SK, Tasnim N, Ahmadi-Vand Z, Jay M, Gibson DL (2015) Methods for improving human gut microbiome data by reducing variability through sample processing and storage of stool. PLoS One 10:e0134802. https://doi.org/10.1371/journal.pone.0134802

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. De Cock M, Virgilio M, Vandamme P, Augustinos A, Bourtzis K, Willems A, De Meyer M (2019) Impact of sample preservation and manipulation on insect gut microbiome profiling. A test case with fruit flies (Diptera, Tephritidae). Front Microbiol 10:2833. https://doi.org/10.3389/fmicb.2019.02833

    Article  PubMed  PubMed Central  Google Scholar 

  32. Hammer TJ, Dickerson JC, Fierer N (2015) Evidence-based recommendations on storing and handling specimens for analyses of insect microbiota. Peerj 3:e1190. https://doi.org/10.7717/peerj.1190

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. Schulte MJ, Martin K, Sauerborn J (2006) Effects of azadirachtin injection in litchi trees (Litchi chinensis Sonn.) on the litchi stink bug (Tessaratoma papillosa Drury) in northern Thailand. J Pest Sci 79:241–250. https://doi.org/10.1007/s10340-006-0142-9

    Article  Google Scholar 

  34. Caporaso JG, Lauber CL, Walters WA, Berg-Lyons D, Huntley J, Fierer N, Owens SM, Betley J, Fraser L, Bauer M, Gormley N, Gilbert JA, Smith G, Knight R (2012) Ultra-high-throughput microbial community analysis on the Illumina HiSeq and MiSeq platforms. Isme J 6:1621–1624. https://doi.org/10.1038/ismej.2012.8

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. Frank JA, Reich CI, Sharma S, Weisbaum JS, Wilson BA, Olsen GJ (2008) Critical evaluation of two primers commonly used for amplification of bacterial 16S rRNA genes. Appl Environ Microbiol 74:2461–2470. https://doi.org/10.1128/AEM.02272-07

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. Stackebrandt E, Goodfellow M (1991) Nucleic acid techniques in bacterial systematics. Wiley, Hoboken

    Google Scholar 

  37. Callahan BJ, McMurdie PJ, Rosen MJ, Han AW, Johnson AJA, Holmes SP (2016) DADA2: high-resolution sample inference from Illumina amplicon data. Nat Methods 13:581–583. https://doi.org/10.1038/NMETH.3869

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  38. Bolyen E, Rideout JR, Dillon MR, Bokulich N, Abnet CC, Al-Ghalith GA et al (2019) Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2. Nat Biotechnol 37:852–857. https://doi.org/10.1038/s41587-019-0209-9

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  39. Bokulich NA, Kaehler BD, Rideout JR, Dillon M, Bolyen E, Knight R, Huttley GA, Caporaso JG (2018) Optimizing taxonomic classification of marker-gene amplicon sequences with QIIME 2’s q2-feature-classifier plugin. Microbiome 6:90. https://doi.org/10.1186/s40168-018-0470-z

    Article  PubMed  PubMed Central  Google Scholar 

  40. Ginestet C (2011) ggplot2: Elegant Graphics for Data Analysis. J R Stat Soc A Stat 174:245–245. https://doi.org/10.1111/j.1467-985X.2010.00676_9.x

    Article  Google Scholar 

  41. Kelly BJ, Gross R, Bittinger K, Sherrill-Mix S, Lewis JD, Collman RG, Bushman FD, Li HZ (2015) Power and sample-size estimation for microbiome studies using pairwise distances and PERMANOVA. Bioinformatics 31:2461–2468. https://doi.org/10.1093/bioinformatics/btv183

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. Duron O, Noel V (2016) A wide diversity of Pantoea lineages are engaged in mutualistic symbiosis and cospeciation processes with stinkbugs. Environ Microbiol Rep 8:715–727. https://doi.org/10.1111/1758-2229.12432

    Article  PubMed  Google Scholar 

  43. Hosokawa T, Ishii Y, Nikoh N, Fujie M, Satoh N, Fukatsu T (2016) Obligate bacterial mutualists evolving from environmental bacteria in natural insect populations. Nat Microbiol 1:15011. https://doi.org/10.1038/NMICROBIOL.2015.11

    Article  CAS  PubMed  Google Scholar 

  44. Kashkouli M, Castelli M, Floriano AM, Bandi C, Epis S, Fathipour Y, Mehrabadi M, Sassera D (2020) Characterization of a novel Pantoea symbiont allows inference of a pattern of convergent genome reduction in bacteria associated with Pentatomidae. Environ Microbiol 23:36–50. https://doi.org/10.1111/1462-2920.15169

    Article  CAS  PubMed  Google Scholar 

  45. Grimaldi D, Engel MS (2005) Evolution of the insects. Cambridge University Press, Cambridge

    Google Scholar 

  46. Bauer E, Kaltenpoth M, Salem H (2020) Minimal fermentative metabolism fuels extracellular symbiont in a leaf beetle. Isme J 14:866–870. https://doi.org/10.1038/s41396-019-0562-1

    Article  CAS  PubMed  Google Scholar 

  47. Binetruy F, Buysse M, Lejarre Q, Barosi R, Villa M, Rahola N, Paupy C, Ayala D, Duron O (2020) Microbial community structure reveals instability of nutritional symbiosis during the evolutionary radiation of Amblyomma ticks. Mol Ecol 29:1016–1029. https://doi.org/10.1111/mec.15373

    Article  PubMed  Google Scholar 

  48. Lam TYC, Mei R, Wu ZY, Lee PKH, Liu WT, Lee PH (2020) Superior resolution characterisation of microbial diversity in anaerobic digesters using full-length 16S rRNA gene amplicon sequencing. Water Res 178:115815. https://doi.org/10.1016/j.watres.2020.115815

    Article  CAS  PubMed  Google Scholar 

  49. Brennan CA, Garrett WS (2019) Fusobacterium nucleatum – symbiont, opportunist and oncobacterium. Nat Rev Microbiol 17:156–166. https://doi.org/10.1038/s41579-018-0129-6

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  50. Flemming HC, Wuertz S (2019) Bacteria and archaea on Earth and their abundance in biofilms. Nat Rev Microbiol 17:247–260. https://doi.org/10.1038/s41579-019-0158-9

    Article  CAS  PubMed  Google Scholar 

Download references

Funding

This work was supported by the National Natural Science Foundation of China (Nos. 31222051 and 31772425) and Science and Technology Program of Guangzhou, China.

Author information

Authors and Affiliations

  1. State Key Laboratory of Biocontrol, Sun Yat-sen University, Guangzhou, 510275, Guangdong, China

    Zi-Wen Yang, Yu Men, Jing Zhang, Zhi-Hui Liu, Jiu-Yang Luo, Yan-Hui Wang, Wen-Jun Li & Qiang Xie

  2. School of Life Sciences, Sun Yat-sen University, Guangzhou, 510275, Guangdong, China

    Zi-Wen Yang, Yu Men, Jing Zhang, Zhi-Hui Liu, Jiu-Yang Luo, Yan-Hui Wang, Wen-Jun Li & Qiang Xie

  3. College of Life Sciences, Nankai University, Tianjin, 300071, China

    Jiu-Yang Luo

  4. Guangdong Provincial Key Laboratory of Plant Resources and Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Sun Yat-sen University, 510275, Guangzhou, China

    Wen-Jun Li

Authors
  1. Zi-Wen Yang
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Yu Men
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Jing Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Zhi-Hui Liu
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Jiu-Yang Luo
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Yan-Hui Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Wen-Jun Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Qiang Xie
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

Conceptualization: Q.X.; methodology: Z.-W.Y.; formal analysis and investigation: Z.-W.Y., Y.M., J.Z., Z.-H.L., J.-Y.L., and Y.-H.W.; writing—original draft preparation: Z.-W.Y. and Y.M.; writing—review and editing: Q.X. and W.-J.L.; funding acquisition: Q.X. and Y.-H.W.; supervision: Q.X.

Corresponding authors

Correspondence to Wen-Jun Li or Qiang Xie.

Ethics declarations

Ethics approval

Not applicable

Consent to participate

Not applicable

Consent for publication

Not applicable

Conflict of interest

The authors declare that they have no conflicts of interest.

Supplementary Information

ESM 1

(PDF 510 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Yang, ZW., Men, Y., Zhang, J. et al. Evaluation of Sample Preservation Approaches for Better Insect Microbiome Research According to Next-Generation and Third-Generation Sequencing. Microb Ecol 82, 971–980 (2021). https://doi.org/10.1007/s00248-021-01727-6

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00248-021-01727-6

Keywords

Search

Navigation