Methodological Insight Into Mosquito Microbiome Studies

. 2020 ; 10 () : 86. [epub] 20200317

Jazyk angličtina Země Švýcarsko Médium electronic-ecollection

Typ dokumentu časopisecké články, práce podpořená grantem

Perzistentní odkaz   https://www.medvik.cz/link/pmid32257962

Symbiotic bacteria affect competence for pathogen transmission in insect vectors, including mosquitoes. However, knowledge on mosquito-microbiome-pathogen interactions remains limited, largely due to methodological reasons. The current, cost-effective practice of sample pooling used in mosquito surveillance and epidemiology prevents correlation of individual traits (i.e., microbiome profile) and infection status. Moreover, many mosquito studies employ laboratory-reared colonies that do not necessarily reflect the natural microbiome composition and variation in wild populations. As a consequence, epidemiological and microbiome studies in mosquitoes are to some extent uncoupled, and the interactions among pathogens, microbiomes, and natural mosquito populations remain poorly understood. This study focuses on the effect the pooling practice poses on mosquito microbiome profiles, and tests different approaches to find an optimized low-cost methodology for extensive sampling while allowing for accurate, individual-level microbiome studies. We tested the effect of pooling by comparing wild-caught, individually processed mosquitoes with pooled samples. With individual mosquitoes, we also tested two methodological aspects that directly affect the cost and feasibility of broad-scale molecular studies: sample preservation and tissue dissection. Pooling affected both alpha- and beta-diversity measures of the microbiome, highlighting the importance of using individual samples when possible. Both RNA and DNA yields were higher when using inexpensive reagents such as NAP (nucleic acid preservation) buffer or absolute ethanol, without freezing for short-term storage. Microbiome alpha- and beta-diversity did not show overall significant differences between the tested treatments compared to the controls (freshly extracted samples or dissected guts). However, the use of standardized protocols is highly recommended to avoid methodological bias in the data.

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Aguirre M., Ramiro-Garcia J., Koenen M. E., Venema K. (2014). To pool or not to pool? Impact of the use of individual and pooled fecal samples for in vitro fermentation studies. J. Microbiol. Methods 107, 1–7. 10.1016/j.mimet.2014.08.022 PubMed DOI

Astrid T., Margit E., Leopold F. (2016). Ethanol: a simple and effective RNA-preservation for freshwater insects living in remote habitats. Limnol. Oceanogr. Methods 14, 186–195. 10.1002/lom3.10079 DOI

Binetruy F., Dupraz M., Buysse M., Duron O. (2019). Surface sterilization methods impact measures of internal microbial diversity in ticks. Parasit. Vectors 12:268. 10.1186/s13071-019-3517-5 PubMed DOI PMC

Bokulich N. A., Subramanian S., Faith J. J., Gevers D., Gordon J. I., Knight R., et al. . (2013). Quality-filtering vastly improves diversity estimates from Illumina amplicon sequencing. Nat. Methods 10, 57–59. 10.1038/nmeth.2276 PubMed DOI PMC

Bordenstein S. R., Theis K. R. (2015). Host biology in light of the microbiome: ten principles of holobionts and hologenomes. PLoS Biol. 13:e1002226. 10.1371/journal.pbio.1002226 PubMed DOI PMC

Čabanová V., Šikutová S., Straková P., Šebesta O., Vichová B., Zubríková D., et al. . (2019). Co-circulation of West Nile and Usutu flaviviruses in mosquitoes in slovakia, 2018. Viruses 11:639. 10.3390/v11070639 PubMed DOI PMC

Camacho C., Coulouris G., Avagyan V., Ma N., Papadopoulos J., Bealer K., et al. . (2009). BLAST+: architecture and applications. BMC Bioinform. 10:421. 10.1186/1471-2105-10-421 PubMed DOI PMC

Camacho-Sanchez M., Burraco P., Gomez-Mestre I., Leonard J. A. (2013). Preservation of RNA and DNA from mammal samples under field conditions. Mol. Ecol. Resour. 13, 663–673. 10.1111/1755-0998.12108 PubMed DOI

Camacho-Sanchez M., Quintanilla I., Hawkins M. T. R., Tuh F. Y. Y., Wells K., Maldonado J. E., et al. (2018). Interglacial refugia on tropical mountains: novel insights from the summit rat (Rattus baluensis), a Borneo mountain endemic. Divers. Distrib. 24, 1252–1266. 10.1111/ddi.12761 DOI

Caporaso J. G., Bittinger K., Bushman F. D., deSantis T. Z., Andersen G. L., Knight R. (2010a). PyNAST: a flexible tool for aligning sequences to a template alignment. Bioinformatics 26, 266–267. 10.1093/bioinformatics/btp636 PubMed DOI PMC

Caporaso J. G., Kuczynski J., Stombaugh J., Bittinger K., Bushman F. D., Costello E. K., et al. . (2010b). QIIME allows analysis of high-throughput community sequencing data. Nat. Methods 7, 335–336. 10.1038/nmeth.f.303 PubMed DOI PMC

Chaisiri K., Gill A. C., Stekolnikov A. A., Hinjoy S., McGarry J. W., Darby A. C., et al. (2019). Ecological and microbiological diversity of chigger mites, including vectors of scrub typhus, on small mammals across stratified habitats in Thailand. Animal Microbiome 1:18 10.1101/523845 PubMed DOI PMC

Clow K. M., Weese J. S., Rousseau J., Jardine C. M. (2018). Microbiota of field-collected Ixodes scapularis and Dermacentor variabilis from eastern and southern Ontario, Canada. Ticks Tick-Borne Dis. 9, 235–244. 10.1016/j.ttbdis.2017.09.009 PubMed DOI

Conway J. R., Lex A., Gehlenborg N. (2017). UpSetR: an R package for the visualization of intersecting sets and their properties. Bioinformatics 33, 2938–2940. 10.1093/bioinformatics/btx364 PubMed DOI PMC

Coon K. L., Vogel K. J., Brown M. R., Strand M. R. (2014). Mosquitoes rely on their gut microbiota for development. Mol. Ecol. 23, 2727–2739. 10.1111/mec.12771 PubMed DOI PMC

Duron O., Bouchon D., Boutin S., Bellamy L., Zhou L., Engelstädter J., et al. (2008). The diversity of reproductive parasites among arthropods: Wolbachia do not walk alone. BMC Biol. 6:27 10.1186/1741-7007-6-27 PubMed DOI PMC

Edgar R. C. (2013). UPARSE: highly accurate OTU sequences from microbial amplicon reads. Nat. Methods 10, 996–998. 10.1038/nmeth.2604 PubMed DOI

Engler O., Savini G., Papa A., Figuerola J., Groschup M. H., Kampen H., et al. . (2013). European surveillance for West nile virus in mosquito populations. Int. J. Environ. Res. Public. Health 10, 4869–4895. 10.3390/ijerph10104869 PubMed DOI PMC

Guégan M., Zouache K., Démichel C., Minard G., Tran van V., Potier P., et al. . (2018). The mosquito holobiont: fresh insight into mosquito-microbiota interactions. Microbiome 6:49. 10.1186/s40168-018-0435-2 PubMed DOI PMC

Hammer T. J., Dickerson J. C., Fierer N. (2015). Evidence-based recommendations on storing and handling specimens for analyses of insect microbiota. PeerJ 3:e1190. 10.7717/peerj.1190 PubMed DOI PMC

Hegde S., Khanipov K., Albayrak L., Golovko G., Pimenova M., Saldaña M. A., et al. . (2018). Microbiome interaction networks and community structure from laboratory-reared and field-collected Aedes aegypti, Aedes albopictus, and Culex quinquefasciatus mosquito vectors. Front. Microbiol. 9:2160. 10.3389/fmicb.2018.02160 PubMed DOI PMC

Johnson N., Fernández de Marco M., Giovannini A., Ippoliti C., Danzetta M. L., Svartz G., et al. . (2018). Emerging mosquito-borne threats and the response from European and eastern Mediterranean countries. Int. J. Environ. Res. Public. Health 15:2775. 10.3390/ijerph15122775 PubMed DOI PMC

Kampen H., Medlock J. M., Vaux A. G., Koenraadt C. J., van Vliet A. J., Bartumeus F., et al. . (2015). Approaches to passive mosquito surveillance in the EU. Parasit. Vectors 8:9. 10.1186/s13071-014-0604-5 PubMed DOI PMC

Knight R., Vrbanac A., Taylor B. C., Aksenov A., Callewaert C., Debelius J., et al. . (2018). Best practices for analysing microbiomes. Nat. Rev. Microbiol. 16, 410–422. 10.1038/s41579-018-0029-9 PubMed DOI

McMurdie P., Paulson J. (2019). Biomformat: An Interface Package for the Biom File Format. Available online at: http://biom-format.org/.

Menke S., Gillingham M. A. F., Wilhelm K., Sommer S. (2017). Home-made cost effective preservation buffer is a better alternative to commercial preservation methods for microbiome research. Front. Microbiol. 8:102. 10.3389/fmicb.2017.00102 PubMed DOI PMC

Minard G., Mavingui P., Moro C. V. (2013). Diversity and function of bacterial microbiota in the mosquito holobiont. Parasit. Vectors 6:146. 10.1186/1756-3305-6-146 PubMed DOI PMC

Montero-Mendieta S., Grabherr M., Lantz H., la Riva I. D., Leonard J. A., Webster M. T., et al. . (2017). A practical guide to build de-novo assemblies for single tissues of non-model organisms: the example of a neotropical frog. PeerJ. 5:e3702. 10.7717/peerj.3702 PubMed DOI PMC

Muturi E. J., Dunlap C., Ramirez J. L., Rooney A. P., Kim C.-H. (2019). Host blood-meal source has a strong impact on gut microbiota of Aedes aegypti. FEMS Microbiol. Ecol. 95, 1–9. 10.1093/femsec/fiy213 PubMed DOI

Muturi E. J., Ramirez J. L., Rooney A. P., Kim C.-H. (2017). Comparative analysis of gut microbiota of mosquito communities in central Illinois. PLoS Negl. Trop. Dis. 11:e0005377. 10.1371/journal.pntd.0005377 PubMed DOI PMC

Niang E. H. A., Bassene H., Fenollar F., Mediannikov O. (2018). Biological control of mosquito-borne diseases: the potential of Wolbachia-based interventions in an IVM framework. J. Trop. Med. 2018:1470459. 10.1155/2018/1470459 PubMed DOI PMC

Nováková E., Woodhams D. C., Rodríguez-Ruano S. M., Brucker R. M., Leff J. W., Maharaj A., et al. . (2017). Mosquito microbiome dynamics, a background for prevalence and seasonality of West Nile Virus. Front. Microbiol. 8:526. 10.3389/fmicb.2017.00526 PubMed DOI PMC

Oksanen J., Blanchet F. G., Kindt R., Legendre P., Minchin P. R., O'Hara R. B., et al. (2013). Vegan: Community Ecology Package. The Comprehensive R Archive Network (CRAN). Available online at: http://CRAN.R-project.org/package=vegan (accessed June 27, 2014).

O'Neill S. L. (2018). “The use of Wolbachia by the world mosquito Program to interrupt transmission of Aedes aegypti transmitted viruses,” in Dengue and Zika: Control and Antiviral Treatment Strategies, eds R. Hilgenfeld and S. G. Vasudevan (Singapore: Springer Singapore; ), 355–360. 10.1007/978-981-10-8727-1_24 PubMed DOI

Palmer W. H., Varghese F. S., van Rij R. P. (2018). Natural variation in resistance to virus infection in dipteran insects. Viruses 10:118. 10.3390/v10030118 PubMed DOI PMC

Pruesse E., Quast C., Knittel K., Fuchs B. M., Ludwig W., Peplies J., et al. . (2007). SILVA: a comprehensive online resource for quality checked and aligned ribosomal RNA sequence data compatible with ARB. Nucleic Acids Res. 35, 7188–7196. 10.1093/nar/gkm864 PubMed DOI PMC

R Development Core Team (2014). R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing Vienna, Austria. Available online at: http://www.R-project.org/ (accessed June 27, 2014).

Rodríguez-Ruano S. M., Škochová V., Rego R. O. M., Schmidt J. O., Roachell W., Hypša V., et al. . (2018). Microbiomes of North American Triatominae: the grounds for Chagas disease epidemiology. Front. Microbiol. 9:1167. 10.3389/fmicb.2018.01167 PubMed DOI PMC

Saldaña M. A., Hegde S., Hughes G. L. (2017). Microbial control of arthropod-borne disease. Mem. Inst. Oswaldo Cruz. 112, 81–93. 10.1590/0074-02760160373 PubMed DOI PMC

Segata N., Baldini F., Pompon J., Garrett W. S., Truong D. T., Dabiré R. K., et al. . (2016). The reproductive tracts of two malaria vectors are populated by a core microbiome and by gender- and swarm-enriched microbial biomarkers. Sci. Rep. 6:24207. 10.1038/srep24207 PubMed DOI PMC

Tsilimigras M. C. B., Fodor A. A. (2016). Compositional data analysis of the microbiome: fundamentals, tools, and challenges. Ann. Epidemiol. 26, 330–335. 10.1016/j.annepidem.2016.03.002 PubMed DOI

Weiss S., Xu Z. Z., Peddada S., Amir A., Bittinger K., Gonzalez A., et al. . (2017). Normalization and microbial differential abundance strategies depend upon data characteristics. Microbiome 5:27. 10.1186/s40168-017-0237-y PubMed DOI PMC

Whitaker M. R. L., Salzman S., Sanders J., Kaltenpoth M., Pierce N. E. (2016). Microbial communities of Lycaenid butterflies do not correlate with larval diet. Front. Microbiol. 7:1920 10.3389/fmicb.2016.01920 PubMed DOI PMC

Wickham H. (2009). Ggplot2: Elegant Graphics for Data Analysis. New York, NY: Springer-Verlag.

Wong A. C.-N., Chaston J. M., Douglas A. E. (2013). The inconstant gut microbiota of Drosophila species revealed by 16S rRNA gene analysis. ISME J. 7, 1922–1932. 10.1038/ismej.2013.86 PubMed DOI PMC

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