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      Parasitism causes changes in caterpillar odours and associated bacterial communities with consequences for host-location by a hyperparasitoid

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          Abstract

          Microorganisms living in and on macroorganisms may produce microbial volatile compounds (mVOCs) that characterise organismal odours. The mVOCs might thereby provide a reliable cue to carnivorous enemies in locating their host or prey. Parasitism by parasitoid wasps might alter the microbiome of their caterpillar host, affecting organismal odours and interactions with insects of higher trophic levels such as hyperparasitoids. Hyperparasitoids parasitise larvae or pupae of parasitoids, which are often concealed or inconspicuous. Odours of parasitised caterpillars aid them to locate their host, but the origin of these odours and its relationship to the caterpillar microbiome are unknown. Here, we analysed the odours and microbiome of the large cabbage white caterpillar Pieris brassicae in relation to parasitism by its endoparasitoid Cotesia glomerata. We identified how bacterial presence in and on the caterpillars is correlated with caterpillar odours and tested the attractiveness of parasitised and unparasitised caterpillars to the hyperparasitoid Baryscapus galactopus. We manipulated the presence of the external microbiome and the transient internal microbiome of caterpillars to identify the microbial origin of odours. We found that parasitism by C. glomerata led to the production of five characteristic volatile products and significantly affected the internal and external microbiome of the caterpillar, which were both found to have a significant correlation with caterpillar odours. The preference of the hyperparasitoid was correlated with the presence of the external microbiome. Likely, the changes in external microbiome and body odour after parasitism were driven by the resident internal microbiome of caterpillars, where the bacterium Wolbachia sp. was only present after parasitism. Micro-injection of Wolbachia in unparasitised caterpillars increased hyperparasitoid attraction to the caterpillars compared to untreated caterpillars, while no differences were found compared to parasitised caterpillars. In conclusion, our results indicate that host-parasite interactions can affect multi-trophic interactions and hyperparasitoid olfaction through alterations of the microbiome.

          Author summary

          Bacteria living in and on macroorganisms produce the majority of their odours and thereby play an essential role in species interactions. For example, the hyperparasitoid enemies of parasitic wasps can reliably use odours of parasitised caterpillars to find the parasitic wasp larvae developing inside the caterpillar. We studied whether parasitism of caterpillars caused changes in caterpillar odours and associated internal and external bacterial communities to elucidate whether specific bacteria are responsible for the odours emitted by parasitised caterpillars. We identified which bacteria corresponded with odour production and whether hyperparasitoids could still find parasitised caterpillars that had their bacterial communities experimentally disrupted. We found that parasitised caterpillars have different odour profiles compared to unparasitised caterpillars and that bacteria in and on caterpillars correspond with these changes. The hyperparasitoid was less attracted to parasitised caterpillars with a disrupted skin microbiome. A characteristic bacterium, Wolbachia sp., which was only found inside parasitised caterpillars, may have initiated changes in the external microbiome and effects on odour emission. Furthermore, we show that micro-injection of Wolbachia in unparasitized caterpillars enhanced hyperparasitoid attraction. Hence, our results indicate that parasitoid wasps indirectly reveal themselves to their hyperparasitoid natural enemies by alteration of the bacterial communities of their host.

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          Most cited references87

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          phyloseq: An R Package for Reproducible Interactive Analysis and Graphics of Microbiome Census Data

          Background The analysis of microbial communities through DNA sequencing brings many challenges: the integration of different types of data with methods from ecology, genetics, phylogenetics, multivariate statistics, visualization and testing. With the increased breadth of experimental designs now being pursued, project-specific statistical analyses are often needed, and these analyses are often difficult (or impossible) for peer researchers to independently reproduce. The vast majority of the requisite tools for performing these analyses reproducibly are already implemented in R and its extensions (packages), but with limited support for high throughput microbiome census data. Results Here we describe a software project, phyloseq, dedicated to the object-oriented representation and analysis of microbiome census data in R. It supports importing data from a variety of common formats, as well as many analysis techniques. These include calibration, filtering, subsetting, agglomeration, multi-table comparisons, diversity analysis, parallelized Fast UniFrac, ordination methods, and production of publication-quality graphics; all in a manner that is easy to document, share, and modify. We show how to apply functions from other R packages to phyloseq-represented data, illustrating the availability of a large number of open source analysis techniques. We discuss the use of phyloseq with tools for reproducible research, a practice common in other fields but still rare in the analysis of highly parallel microbiome census data. We have made available all of the materials necessary to completely reproduce the analysis and figures included in this article, an example of best practices for reproducible research. Conclusions The phyloseq project for R is a new open-source software package, freely available on the web from both GitHub and Bioconductor.
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            Global patterns of 16S rRNA diversity at a depth of millions of sequences per sample.

            The ongoing revolution in high-throughput sequencing continues to democratize the ability of small groups of investigators to map the microbial component of the biosphere. In particular, the coevolution of new sequencing platforms and new software tools allows data acquisition and analysis on an unprecedented scale. Here we report the next stage in this coevolutionary arms race, using the Illumina GAIIx platform to sequence a diverse array of 25 environmental samples and three known "mock communities" at a depth averaging 3.1 million reads per sample. We demonstrate excellent consistency in taxonomic recovery and recapture diversity patterns that were previously reported on the basis of metaanalysis of many studies from the literature (notably, the saline/nonsaline split in environmental samples and the split between host-associated and free-living communities). We also demonstrate that 2,000 Illumina single-end reads are sufficient to recapture the same relationships among samples that we observe with the full dataset. The results thus open up the possibility of conducting large-scale studies analyzing thousands of samples simultaneously to survey microbial communities at an unprecedented spatial and temporal resolution.
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              Development of a dual-index sequencing strategy and curation pipeline for analyzing amplicon sequence data on the MiSeq Illumina sequencing platform.

              Rapid advances in sequencing technology have changed the experimental landscape of microbial ecology. In the last 10 years, the field has moved from sequencing hundreds of 16S rRNA gene fragments per study using clone libraries to the sequencing of millions of fragments per study using next-generation sequencing technologies from 454 and Illumina. As these technologies advance, it is critical to assess the strengths, weaknesses, and overall suitability of these platforms for the interrogation of microbial communities. Here, we present an improved method for sequencing variable regions within the 16S rRNA gene using Illumina's MiSeq platform, which is currently capable of producing paired 250-nucleotide reads. We evaluated three overlapping regions of the 16S rRNA gene that vary in length (i.e., V34, V4, and V45) by resequencing a mock community and natural samples from human feces, mouse feces, and soil. By titrating the concentration of 16S rRNA gene amplicons applied to the flow cell and using a quality score-based approach to correct discrepancies between reads used to construct contigs, we were able to reduce error rates by as much as two orders of magnitude. Finally, we reprocessed samples from a previous study to demonstrate that large numbers of samples could be multiplexed and sequenced in parallel with shotgun metagenomes. These analyses demonstrate that our approach can provide data that are at least as good as that generated by the 454 platform while providing considerably higher sequencing coverage for a fraction of the cost.
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                Author and article information

                Contributors
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: InvestigationRole: MethodologyRole: ValidationRole: VisualizationRole: Writing – original draftRole: Writing – review & editing
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: InvestigationRole: MethodologyRole: VisualizationRole: Writing – original draftRole: Writing – review & editing
                Role: Formal analysisRole: InvestigationRole: MethodologyRole: ValidationRole: VisualizationRole: Writing – review & editing
                Role: ConceptualizationRole: InvestigationRole: MethodologyRole: Writing – review & editing
                Role: Formal analysisRole: InvestigationRole: MethodologyRole: VisualizationRole: Writing – review & editing
                Role: Data curationRole: Formal analysisRole: SoftwareRole: Writing – review & editing
                Role: ConceptualizationRole: Data curationRole: Funding acquisitionRole: Project administrationRole: SupervisionRole: Writing – review & editing
                Role: ConceptualizationRole: Formal analysisRole: Funding acquisitionRole: SupervisionRole: VisualizationRole: Writing – review & editing
                Role: ConceptualizationRole: Funding acquisitionRole: Project administrationRole: ResourcesRole: SupervisionRole: ValidationRole: Writing – review & editing
                Role: ConceptualizationRole: SupervisionRole: ValidationRole: Writing – original draftRole: Writing – review & editing
                Role: Editor
                Journal
                PLoS Pathog
                PLoS Pathog
                plos
                PLOS Pathogens
                Public Library of Science (San Francisco, CA USA )
                1553-7366
                1553-7374
                22 March 2023
                March 2023
                : 19
                : 3
                : e1011262
                Affiliations
                [1 ] Laboratory of Entomology, Wageningen University & Research, Wageningen, The Netherlands
                [2 ] CMPG Laboratory for Process Microbial Ecology and Bioinspirational Management (PME&BIM), Department M2S, KU Leuven, Leuven, Belgium
                [3 ] Leuven Plant Institute (LPI), KU Leuven, Leuven, Belgium
                [4 ] Laboratory of Plant Conservation and Population Biology, Biology Department, KU Leuven, Leuven, Belgium
                University of California Riverside, UNITED STATES
                Author notes

                The authors have declared that no competing interests exist.

                Author information
                https://orcid.org/0000-0002-8148-9586
                https://orcid.org/0000-0002-4029-9882
                https://orcid.org/0000-0001-8838-7876
                https://orcid.org/0009-0007-5588-7226
                https://orcid.org/0000-0002-9598-4510
                https://orcid.org/0000-0001-7675-5301
                https://orcid.org/0000-0002-7698-6641
                https://orcid.org/ 0000-0001-9600-5794
                https://orcid.org/0000-0001-8565-8896
                https://orcid.org/0000-0003-3285-613X
                Article
                PPATHOGENS-D-22-01701
                10.1371/journal.ppat.1011262
                10069771
                36947551
                e106c3a1-2243-4dbe-96c9-155753efbd3f
                © 2023 Bourne 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.

                History
                : 30 September 2022
                : 2 March 2023
                Page count
                Figures: 8, Tables: 1, Pages: 32
                Funding
                Funded by: funder-id http://dx.doi.org/10.13039/501100003246, Nederlandse Organisatie voor Wetenschappelijk Onderzoek;
                Award ID: ALWOP.343
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/501100003246, Nederlandse Organisatie voor Wetenschappelijk Onderzoek;
                Award ID: ALWOP.368
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/501100003130, Fonds Wetenschappelijk Onderzoek;
                Award ID: G.0961.19N
                Award Recipient :
                This work was supported by NWO (ALW Open Programme ALWOP.343 to M.D., Spinoza award SPI 87-313 to M.D., and ALW Open Programme ALWOP.368 to E.H.P) and the Flemish Fund for Scientific Research (FWO; G.0961.19N to B.L. and H.J.). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Biology and Life Sciences
                Zoology
                Entomology
                Insects
                Moths and Butterflies
                Caterpillars
                Biology and Life Sciences
                Organisms
                Eukaryota
                Animals
                Invertebrates
                Arthropoda
                Insects
                Moths and Butterflies
                Caterpillars
                Biology and Life Sciences
                Zoology
                Animals
                Invertebrates
                Arthropoda
                Insects
                Moths and Butterflies
                Caterpillars
                Biology and Life Sciences
                Microbiology
                Medical Microbiology
                Microbiome
                Biology and Life Sciences
                Genetics
                Genomics
                Microbial Genomics
                Microbiome
                Biology and Life Sciences
                Microbiology
                Microbial Genomics
                Microbiome
                Biology and Life Sciences
                Species Interactions
                Parasitism
                Biology and Life Sciences
                Ecology
                Community Ecology
                Trophic Interactions
                Parasitism
                Ecology and Environmental Sciences
                Ecology
                Community Ecology
                Trophic Interactions
                Parasitism
                Biology and Life Sciences
                Organisms
                Bacteria
                Biology and Life Sciences
                Organisms
                Bacteria
                Wolbachia
                Biology and Life Sciences
                Developmental Biology
                Life Cycles
                Larvae
                Biology and Life Sciences
                Zoology
                Entomology
                Insects
                Hymenoptera
                Wasps
                Biology and Life Sciences
                Organisms
                Eukaryota
                Animals
                Invertebrates
                Arthropoda
                Insects
                Hymenoptera
                Wasps
                Biology and Life Sciences
                Zoology
                Animals
                Invertebrates
                Arthropoda
                Insects
                Hymenoptera
                Wasps
                Biology and Life Sciences
                Organisms
                Bacteria
                Gut Bacteria
                Custom metadata
                vor-update-to-uncorrected-proof
                2023-04-03
                The sequences obtained in this study were deposited in the Sequence Read Archive (SRA) at NCBI under Bioproject PRJNA878850. zOTU count data per sample for the internal and external microbiome of caterpillars ( 10.6084/m9.figshare.21253455), the corresponding measured VOCs ( 10.6084/m9.figshare.21253518) and the outcome of choice tests ( 10.6084/m9.figshare.21253524) and no-choice tests ( 10.6084/m9.figshare.22133318) are available on Figshare.

                Infectious disease & Microbiology
                Infectious disease & Microbiology

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