Abstract Insects are frequently associated with bacteria that can have significant ecological and evolutionary impacts on their hosts. To date, few studies have examined the influence of environmental factors to microbiome composition of aphids. The current work assessed the diversity of bacterial communities of five cereal aphid species (Sitobion avenae, Rhopalosiphum padi, R. maidis, Sipha maydis and Diuraphis noxia) collected across Morocco, covering a wide range of environmental conditions. We aimed to test whether symbiont combinations are host or environment specific. Deep 16S rRNA sequencing enabled us to identify 17 bacterial operational taxonomic units (OTUs). The obligate symbiont Buchnera aphidicola was represented by five OTUs with multiple haplotypes in many single samples. Facultative endosymbionts were presented by a high prevalence of Regiella insecticola and Serratia symbiotica in S. avenae and Si. maydis, respectively. In addition to these symbiotic partners, Pseudomonas, Acinetobacter, Pantoea, Erwinia and Staphyloccocus were also identified in aphids, suggesting that the aphid microbiome is not limited to the presence of endosymbiotic bacteria. Beside a significant association between host species and bacterial communities, an inverse correlation was also found between altitude and α-diversity. Overall, our results support that symbiont combinations are mainly host specific. bacterial community, symbionts, cereal aphids, host plants, geographical distribution, Morocco INTRODUCTION Bacterial symbionts are widespread among arthropods and are considered as major players in the ecology and evolution of their hosts. Aphids (Hemiptera: Aphididae) in particular are host to a diverse community of symbionts and constitute one of the most studied model system for the investigation of bacteria–arthropod symbiosis. By feeding on phloem and transmitting plant diseases aphids are insect pests that can cause significant damages to numerous economically important crops around the world (Blackman and Eastop 2008; Dedryver, Le Ralec and Fabre 2010). The ecological success of these insects is largely due to their ability to reproduce asexually, but also to engage in symbiotic associations with many beneficial intracellular bacteria (Oliver et al.2010; Ferrari and Vavre 2011). Aphids typically harbor only one obligate symbiont, Buchnera aphidicola, that provides essential amino acids and vitamins that cannot be obtained in sufficient quantities from the phloem sap diet (Douglas 1998; Nakabachi and Ishikawa 1999). Buchnera aphidicola is hosted in specialized cells called primary bacteriocytes and is strictly vertically transmitted from mother to offspring. In addition to B. aphidicola, aphids may harbor an array of facultative symbionts that are not required for host survival, but that can be mutualistic in the context of various ecological interactions (Oliver et al.2010; Feldhaar 2011). Usually occurring in a fraction of host populations (Oliver et al.2010), these facultative bacteria display a great diversity of tissue tropisms (Moran et al.2005), and can experience occasional horizontal transfers within and between host species in addition to vertical transmission (Sandström et al.2001; Henry et al.2013). The existence of facultative aphid symbionts has been known for many years (Buchner 1965), but their functional diversity has only recently been explored more thoroughly. Ecological benefits associated with these microorganisms in aphids include defense against pathogens and natural enemies (Oliver et al.2003; Oliver, Moran and Hunter 2005; Łukasik et al.2013b), body color changes (Tsuchida et al.2010), heat tolerance (Burke, Fiehn and Moran 2009), host plant use (Tsuchida, Koga and Fukatsu 2004) and manipulation of host reproduction (Simon et al.2011). The bacterial community usually described in aphids include Gammaproteobacteria [e.g. Arsenophonus sp. (Jousselin et al.2013), Regiella insecticola (Scarborough, Ferrari and Godfray 2005), Serratia symbiotica (Burke and Moran 2011), Hamiltonella defensa (Degnan et al.2009), Rickettsiella viridis (Tsuchida et al.2010) and PAXS ‘Pea Aphid X-type Symbiont’ (Guay et al.2009; Ferrari et al.2012)], Alphaproteobacteria [e.g. the genera Rickettsia (Sakurai et al.2005), and Wolbachia (Gómez-Valero et al.2004)] and Mollicutes of Spiroplasma genus (Fukatsu et al.2001). This diversity of symbionts in aphids has been studied within a relatively narrow host range considering that most studies were based on the pea aphid Acyrthosiphon pisum and some aphids belonging to the genera Cinara and Aphis. Moreover, focusing on facultative symbionts often leads researchers to overlook other parts of the aphid microbiome, such as extracellular bacteria found in the aphid digestive tract. These include beneficial gut symbionts, pathogens, phytopathogens and environmental contaminants (Harada et al.1997; Sevim, Çelebi and Sevim 2012; Gauthier et al.2015; Grigorescu et al.2017) that can also have ecological and evolutionary impacts on their hosts. Bacteria found within the aphid digestive tract, for example, are expected to be involved in host nutrition, host resistance against pathogens and host vectorial competence (Dillon and Dillon 2004; Cirimotich et al.2011; Engel and Moran 2013). A more extensive characterization of the aphid microbiome and the impact of environmental factors on bacterial communities is therefore required to improve our understanding of the complex interactions that modulate essential aspects of the life cycle of these agriculturally important insects. Studies suggest that the whole set of microorganisms living in association with the aphid (i.e. their microbiote) is related to the type of environment they encounter and the selection pressures to which the whole aphid microbiote has been exposed (Tsuchida, Koga and Fukatsu 2004; Oliver et al.2010; Tsuchida et al.2010). On the one hand, correlations between the prevalence of some symbiotic bacteria in aphids and environmental factors have been reported, such as the host plant utilization (Tsuchida, Koga and Fukatsu 2004; McLean et al.2011; Henry et al.2013, 2015; Hansen and Moran 2014) and some climatic factors (Chen, Montllor and Purcell 2000; Henry et al.2013). On the other hand, some studies state that the host species is the major structuring factor of the aphid-associated symbiotic community (Haynes et al.2003; Jones et al.2011; Sepúlveda et al.2017). There is currently no clear consensus concerning the relative contribution of these factors in the structuration of the microbial diversity harbored by these phytophagous insects. This is partially explained by the fact that most studies have focused on the pea aphid A. pisum in temperate regions and there is virtually no large-scale data available for other geoclimatic regimes and a lack of information regarding the microbial diversity variation among aphid species (Brady et al.2013). A sampling effort, taking into account the diversity of host aphids and of geoclimatic regimes, is therefore needed to better appreciate the complexity of the factors structuring the bacterial communities associated with aphid populations. Our hypothesis is that specific combinations of associated bacteria are more frequently found in unrelated aphids that share the same environment. To test this hypothesis, we carried out a large-scale field study across Morocco to analyze the diversity and the distribution of bacterial communities found in populations of five cereal aphid species. The sampling process was carried out in contrasted bioclimatic zones to investigate the role of different environmental conditions on the structuring of bacterial communities. The 16S rRNA amplicon Illumina sequencing approach was used to assess the composition of the microbiome associated with our sampled aphids. MATERIALS AND METHODS Sample collection Five aphid species, Sitobion avenae, Rhopalosiphum padi, R. maidis, Sipha maydis and Diuraphis noxia (Hemiptera: Aphididae), were collected between April and May 2014 on three common cereals cultivated in Morocco (Triticum turgidum, T. aestivum and Hordeum vulgare). A total of 54 locations were sampled covering a wide diversity of geographical and climatic conditions in Morocco (Fig. 1, Fig. S1 and Table S1, Supporting Information). Aphid collection only consisted of three wingless parthenogenetic adult females that were preserved in 95% ethanol at 4°C until use. A total of 129 aphid colonies were sampled. For each sample host plant, geographical coordinates and altitude were recorded. Factors such as temperature, rainfall and bioclimatic class were extrapolated from maps made by Mokhtari et al. (2013) using ESRI-ArcMap 10.2.2. Figure 1. View large Download slide Geographical location of collection sites of cereal aphid species analyzed in this study. Pie charts depict the locations of the 54 collection sites across Morocco and colors represent the different aphid species collected in each site (for details, see Table S1, Supporting information). Aphid species abbreviations: DN: Diuraphis noxia, RM: Rhopalosiphum maidis, RP: Rhopalosiphum padi, SA: Sitobion avenae and SM: Sipha maydis. Figure 1. View large Download slide Geographical location of collection sites of cereal aphid species analyzed in this study. Pie charts depict the locations of the 54 collection sites across Morocco and colors represent the different aphid species collected in each site (for details, see Table S1, Supporting information). Aphid species abbreviations: DN: Diuraphis noxia, RM: Rhopalosiphum maidis, RP: Rhopalosiphum padi, SA: Sitobion avenae and SM: Sipha maydis. DNA extraction, PCR and sequencing Insect samples were first surface-sterilized with 99% ethanol, 10% bleach and rinsed with sterile water as outlined in Medina, Nachappa and Tamborindeguy (2011). The genomic DNA was extracted using the DNeasy Blood & Tissue kit (QIAGEN) following the instructions of the manufacturer. Each DNA extraction was performed on a pool of three individuals from the same colony. DNA extractions were then quantified using a Nanodrop spectrophotometer (Thermo Scientific) and were stored at –20°C (DNA concentration varies between 16.1 and 266.5 ng/μl). After extraction, the genomic 16S rRNA has been diluted using sterilized ultrapure water in equal concentrations (5 ng/μl) from each sample for future step. Sequencing libraries were prepared according to the Illumina MiSeq system instructions 16S workflow. The V3-V4 variable region of the 16S bacterial rRNA gene was amplified using a two-stage PCR protocol. The first-stage PCR (PCR1) amplification use the universal primers of interest region with overhang adapters attached (F: 5΄ TCGTCGGCAGCGTCAGATGTGTATAAGAGACAGCCTACGGGNGGCWGCAG and R: 5΄ GTCTCGTGGGCTCGGAGATGTGTATAAGAGACAGGACTACHVGGGTATCTAATCC) to amplify a 483-bp portion of the V3-V4 region. This step uses a kit 2x KAPA HiFi HotStart ReadyMix in a mixture total volume of 25 μl. The PCR1 was performed under the following conditions: 3 min initial denaturation at 95°C; 25 cycles of denaturation (30 s at 95°C), annealing (30 s at 55°C) and extension (30 s at 72°C); a final extension at 72°C for 5 min. The PCR1 product has been cleaned with AMPure XP beads to purify the 16S V3-V4 amplicon away from free primers and primer dimer species. The second-stage PCR (PCR2) was done with 5 μl PCR1 purified to attach dual indices and Illumina sequencing adapters using the Nextera XT. The second-stage PCR (PCR2) was done with 5 μl purified PCR1 product to attach dual indices and Illumina sequencing adapters using the Nextera XT Index Kit. Different combinations of index (i5 and i7) were used for each sample. The PCR2 was performed under the same conditions of PCR1 with only eight PCR cycles of denaturation/annealing/extension. A clean-up of the PCR2 products with AMPure XP beads has been performed before quantification. PCR2 products were quantified and normalized at 7 ng/μl using PicoGreen dsDNA Quantitation Assay and were generated an equimolar pool (7 ng/μl). Before proceeding to high-throughput sequencing (HTS), the final pool will be quantified by qPCR (kit KAPA SYBR FAST qPCR ABI Prism readymix KK4604) and 7 pM of denatured final pool was loaded on MiSeq reagent kits v3 (600 cycles). The HTS was carried by the GIGA-Research Center of the University of Liège (Belgium) using Illumina MiSeq Technology for paired-end sequencing (2 × 300 bp reads). Negative controls were performed to validate each laboratory step and to identify the possible contaminations (extraction, amplification and sequencing). These negative controls consist of the reaction mixture of this stage except the products containing genetic material. For evaluation of the bacterial diversity associated with body surface of aphids, we also analyzed the ethanol samples in which the insects were preserved after evaporation. Data analysis De novo operational taxonomic unit (OTU) picking was carried out using the UPARSE (Edgar 2013) bioinformatics pipeline. In a first step, forward and reverse sequences from paired-end sequencing data files were merged for each aphid sample (n = 129). A quality filtering step was then applied to keep sequences with an expected number of errors <1.0 and a length > 450 nt. After quality filtering, sequences from all samples were pooled together to make the results of each experiment comparable, as recommended in the UPARSE manual. After dereplication and sorting of all sequences, singletons were discarded and the remaining sequences were clustered into representative OTUs using a radius percentage of 3.0 (i.e., a minimum identity of 97%). The resulting OTUs were scanned to detect and remove chimera using a reference-based filtering with UCHIME and the gold database of the corresponding software. Finally, an OTU table was generated by mapping all quality-filtered sequences from all samples against the non-chimeric OTUs. A second level of quality filtering was carried out in order to discard those OTUs with a number of sequences <0.005% of the total number of sequences, as recommended previously by Navas-Molina et al. (2013). The taxonomic assignment of each OTU was carried out using a local BLAST against the Greengenes database version 13.5 (DeSantis et al.2006). The Greengenes database was divided into subdatabases according to the level of taxonomic definition (genus, family, order, phylum). The taxonomic assignment of each OTU was based on a blast hit at the species, genus, family or order level if a >97%, >95%, >90% or >85% identity was found in the corresponding databases, respectively. Finally, to improve the taxonomic assignment, the representative OTUs were compared to the sequences in GenBank using BLAST. The OTU table and the OTUs taxonomic assignment were the starting point of the downstream statistical analyses which were performed using R software (version 3.1.2., Vienna, Austria). Considering the existing heterogeneity of the sequencing depth between samples, each sample was rarefied to an equal sequencing depth per sample (25 000 reads per sample) before α-diversity analyses. A multiple linear regression model was built in order to assess the impact of aphid species, host plant and environmental factors on α-diversity. Statistical analyses of species absolute counts were performed using negative binomial generalized linear models with the Bioconductor DESeq2 (Love, Huber and Anders 2014) package in R. In this study, this package was used to assess the impact of five environmental factors (1: aphid species; 2: altitude; 3: temperature; 4: host plant; 5: bioclimate) on each bacterial genus abundance. Although DESeq2 was originally designed to detect differentially abundant gene expression from RNA-Seq data, this package has proved to correctly handle metagenomics count data (McMurdie and Holmes 2014) and has recently been used in studies of microbiota (Collins et al.2015; Rosales and Thurber 2015). Wald tests for differential expression were conducted with this package and P-values were adjusted to reach a Benjamini–Hochberg false discovery rate ≤ 0.05 (Benjamini and Hochberg 1995). The phylogenetic analysis was carried out using SeaView v4.6.1 to align sequences and GBlocks v0.91b (Castresana 2000) to remove poorly aligned positions and divergent regions of DNA alignments. GTR + I + G was selected as the best fit evolutionary model using PartitionFinder v1.1.0 (Lanfear et al.2012). The phylogenetic tree was reconstructed using the neighbor joining method with SeaView v4.6.1 and bootstrap values were computed for each branch node (N = 1000). Phylogenetic relationships of bacteria associated with different populations of cereal aphids and representative endosymbionts of other aphids based on 16S rRNA tag sequence similarity were represented. Finally, the accession numbers of NGS sequences and representative 16S rRNA sequences found in cereal aphids during this study are given in Table S2 (Supporting Information). RESULTS Library basic statistics Approximately 25 million bacterial 16S rRNA reads were obtained from the 129 populations (∼32.5 Gb). The assembly of paired sequences resulted in consensus sequences with an average length of 465 bp. The quality-based filtering of the consensus sequences resulted in 12 827 260 high-quality sequences (51.8% of all reads) with an average number of sequences per sample ranging between 50 516 for D. noxia and 104 945 reads for R. padi (Table 1). It is worth noting that only one sample yielded under 25 000 of reads and was therefore excluded by the rarefaction step and not included in later analyses (α diversity). Table 1. Summary of sequencing data. Dn Rm Rp Sa Sm Sum of all samples (n = 6) (n = 25) (n = 46) (n = 46) (n = 6) Raw data Average size (Mb) per sample 121 245 250 269 299 32519 Average number of sequence per sample 92 018 187 656 190 005 204,078 226 492 24730278 After assembly of paired sequences Average size (Mb) per sample 89 174 181 197 218 2358 Average number of sequence per sample 91 025 183 758 186 001 200 778 222 583 24267432 Average of median sequence length (bp) 465 465 465 465 465 After quality filtering Average size (Mb) per sample 24 46 51 50 44 6204 Average number of sequence per sample 50 516 96 048 104 945 103 106 92 103 12827260 Dn Rm Rp Sa Sm Sum of all samples (n = 6) (n = 25) (n = 46) (n = 46) (n = 6) Raw data Average size (Mb) per sample 121 245 250 269 299 32519 Average number of sequence per sample 92 018 187 656 190 005 204,078 226 492 24730278 After assembly of paired sequences Average size (Mb) per sample 89 174 181 197 218 2358 Average number of sequence per sample 91 025 183 758 186 001 200 778 222 583 24267432 Average of median sequence length (bp) 465 465 465 465 465 After quality filtering Average size (Mb) per sample 24 46 51 50 44 6204 Average number of sequence per sample 50 516 96 048 104 945 103 106 92 103 12827260 Aphid species abbreviations: Dn: Diuraphis noxia, Rm: Rhopalosiphum maidis, Rp: Rhopalosiphum padi, Sa: Sitobion avenae and Sm: Sipha maydis. View Large OTU clustering and taxonomic assignment High-quality reads were clustered using >97% sequence similarity into 17 microbial OTUs (Table 2). All OTUs corresponded to two phyla (Proteobacteria and Firmicutes) and three bacterial orders (Enterobacteriales, Pseudomonadales, Bacillales). The cereal aphid species showed microbial profiles dominated by the Enterobacteriale order that includes both primary and facultative endosymbionts. The obligate nutritive endosymbiont B. aphidicola was detected in all aphid samples (100%) and was represented by five OTUs (OTU 1, 2, 3, 4 and 5) that accounted for 96.41% of all reads. OTUs 1, 2, 4 and 5 differed only by 9 to16 bp, whereas OTU3 differed from these OTUs by 28 to 35 bp. Table 2. Taxonomic assignment of OTUs by Greengenes and GenBank, including the three top BLAST hits, GenBank accession numbers and % identity. OTU no. PC. reads Greengenes identification Three closest GenBank matches Taxon Id % Matched sequences/hosts Accession Id % 1 14 289 Buchnera 99.35 Buchnera aphidicola/R. padi M63248.1 99 Buchnera aphidicola/R. maidis JX998123.1 98 Buchnera aphidicola/Myzus mushaensis JX998130.1 98 2 33 785 Buchnera 99.35 Buchnera aphidicola/Sitobion miscanthi KF056923.1 99 Buchnera aphidicola/S. miscanthi HM156635.1 99 Buchnera aphidicola/S. miscanthi HM156630.1 99 3 3140 Buchnera 96.14 Buchnera aphidicola/Sipha elegans JQ269587.1 97 Buchnera aphidicola/Chaitophorus viminalis M63252.1 96 Buchnera aphidicola/Periphyllus diacerivorus JX998117.1 96 4 4637 Buchnera 98.71 Buchnera aphidicola/D. noxia M63251.1 99 Buchnera aphidicola/A. gossypii KT175925.1 98 Buchnera aphidicola/Aphis craccivora EF614236.1 98 5 40 561 Buchnera 99.78 Buchnera aphidicola/R. maidis JX998123.1 99 Buchnera aphidicola/R. maidis M63247.1 99 Buchnera aphidicola/R. padi M63248.1 98 6 0995 Serratia symbiotica 98.92 Serratia symbiotica/Aphis fabae KT176016.1 99 Serratia symbiotica/Cinara alba KP866513.1 99 Serratia symbiotica/Trama caudate LT600349.1 99 7 2389 Candidatus Regiella insecticola 99.35 Regiella insecticola/S. avenae FJ357499.1 99 Regiella insecticola/S. avenae FJ357497.1 99 Regiella insecticola/S. avenae KX500305.1 99 8 0042 Enterobacteriaceae 99.35 Regiella insecticola/S. avenae KT428726.1 99 Regiella insecticola/Periphyllus negundinis KT336582.1 99 Regiella insecticola/A. fabae KT175991.1 99 9 0076 Candidatus Hamiltonella defensa 99.35 Hamiltonella defensa/S. avenae KM036002.1 99 Hamiltonella defensa/Macrosiphum euphorbiae KU196964.1 99 Hamiltonella defensa/S. fragariae KM375936.1 99 10 0016 Pseudomonas viridiflava 99.35 Pseudomonas viridiflava/Cucumis sativus KU686699.1 99 Pseudomonas viridiflava/Brassica oleracea KT825746.1 99 Pseudomonas sp./Citrus sp. HG805788.1 99 11 0014 Pseudomonas veronii 99.35 Pseudomonas sp./Urban Freshwater KR856479.1 99 Pseudomonas fluorescens/Pisum sativum KU312049.1 99 Pseudomonas sp./B. oleracea L. KT825845.1 99 12 0009 Pseudomonas veronii 99.35 Pseudomonas sp./Water KU519713.1 99 Pseudomonas sp./B. oleracea L. KT825753.1 99 Pseudomonas sp./rhizosphere KT441044.1 99 13 0009 Pseudomonas viridiflava 98.28 Pseudomonas sp./B. oleracea L. KT825741.1 99 Pseudomonas putida/Lactuca sativa LN868451.1 99 Pseudomonas oryzihabitans/soil KP890064.1 99 14 0008 Acinetobacter rhizosphaerae 99.14 Acinetobacter sp./Acantholyda posticalis KT715034.1 99 Acinetobacter sp./soil of apple KT452780.1 99 Acinetobacter rhizosphaerae/Rhizosphere HF585056.1 99 15 0014 Erwinia dispersa 98.06 Pantoea agglomerans/Aedes albopictus KU550206.1 99 Pantoea sp./potato rhizosphere KT726368.1 99 Pantoea agglomerans/Primula secundiflora KM891555.1 99 16 0007 Enterobacter cowanii 98.06 Enterobacter aphidicola/pepper KU991850.1 99 Enterobacter aphidicola/cucumber KR265420.1 99 Enterobacter aphidicola/capsicum KR265413.1 99 17 0010 Staphylococcus epidermidis 99.57 Staphylococcus epidermidis/Aedes albopictus KU550237.1 99 Staphylococcus epidermidis/fermented soy KU301333.1 99 Staphylococcus epidermidis/Canna flaccida KU297773.1 99 OTU no. PC. reads Greengenes identification Three closest GenBank matches Taxon Id % Matched sequences/hosts Accession Id % 1 14 289 Buchnera 99.35 Buchnera aphidicola/R. padi M63248.1 99 Buchnera aphidicola/R. maidis JX998123.1 98 Buchnera aphidicola/Myzus mushaensis JX998130.1 98 2 33 785 Buchnera 99.35 Buchnera aphidicola/Sitobion miscanthi KF056923.1 99 Buchnera aphidicola/S. miscanthi HM156635.1 99 Buchnera aphidicola/S. miscanthi HM156630.1 99 3 3140 Buchnera 96.14 Buchnera aphidicola/Sipha elegans JQ269587.1 97 Buchnera aphidicola/Chaitophorus viminalis M63252.1 96 Buchnera aphidicola/Periphyllus diacerivorus JX998117.1 96 4 4637 Buchnera 98.71 Buchnera aphidicola/D. noxia M63251.1 99 Buchnera aphidicola/A. gossypii KT175925.1 98 Buchnera aphidicola/Aphis craccivora EF614236.1 98 5 40 561 Buchnera 99.78 Buchnera aphidicola/R. maidis JX998123.1 99 Buchnera aphidicola/R. maidis M63247.1 99 Buchnera aphidicola/R. padi M63248.1 98 6 0995 Serratia symbiotica 98.92 Serratia symbiotica/Aphis fabae KT176016.1 99 Serratia symbiotica/Cinara alba KP866513.1 99 Serratia symbiotica/Trama caudate LT600349.1 99 7 2389 Candidatus Regiella insecticola 99.35 Regiella insecticola/S. avenae FJ357499.1 99 Regiella insecticola/S. avenae FJ357497.1 99 Regiella insecticola/S. avenae KX500305.1 99 8 0042 Enterobacteriaceae 99.35 Regiella insecticola/S. avenae KT428726.1 99 Regiella insecticola/Periphyllus negundinis KT336582.1 99 Regiella insecticola/A. fabae KT175991.1 99 9 0076 Candidatus Hamiltonella defensa 99.35 Hamiltonella defensa/S. avenae KM036002.1 99 Hamiltonella defensa/Macrosiphum euphorbiae KU196964.1 99 Hamiltonella defensa/S. fragariae KM375936.1 99 10 0016 Pseudomonas viridiflava 99.35 Pseudomonas viridiflava/Cucumis sativus KU686699.1 99 Pseudomonas viridiflava/Brassica oleracea KT825746.1 99 Pseudomonas sp./Citrus sp. HG805788.1 99 11 0014 Pseudomonas veronii 99.35 Pseudomonas sp./Urban Freshwater KR856479.1 99 Pseudomonas fluorescens/Pisum sativum KU312049.1 99 Pseudomonas sp./B. oleracea L. KT825845.1 99 12 0009 Pseudomonas veronii 99.35 Pseudomonas sp./Water KU519713.1 99 Pseudomonas sp./B. oleracea L. KT825753.1 99 Pseudomonas sp./rhizosphere KT441044.1 99 13 0009 Pseudomonas viridiflava 98.28 Pseudomonas sp./B. oleracea L. KT825741.1 99 Pseudomonas putida/Lactuca sativa LN868451.1 99 Pseudomonas oryzihabitans/soil KP890064.1 99 14 0008 Acinetobacter rhizosphaerae 99.14 Acinetobacter sp./Acantholyda posticalis KT715034.1 99 Acinetobacter sp./soil of apple KT452780.1 99 Acinetobacter rhizosphaerae/Rhizosphere HF585056.1 99 15 0014 Erwinia dispersa 98.06 Pantoea agglomerans/Aedes albopictus KU550206.1 99 Pantoea sp./potato rhizosphere KT726368.1 99 Pantoea agglomerans/Primula secundiflora KM891555.1 99 16 0007 Enterobacter cowanii 98.06 Enterobacter aphidicola/pepper KU991850.1 99 Enterobacter aphidicola/cucumber KR265420.1 99 Enterobacter aphidicola/capsicum KR265413.1 99 17 0010 Staphylococcus epidermidis 99.57 Staphylococcus epidermidis/Aedes albopictus KU550237.1 99 Staphylococcus epidermidis/fermented soy KU301333.1 99 Staphylococcus epidermidis/Canna flaccida KU297773.1 99 Id, identity %; PC. Reads, cluster size in % BLAST searches were performed against the NCBI GenBank database on August 2016. View Large The next most abundant OTUs were represented by three known facultative endosymbionts of aphids that account for 3.5% of all reads and were distributed as follows: Re. insecticola (OTUs 7 and 8), Se. symbiotica (OTU 6) and H. defensa (OTU 9). Taxonomic identification of bacterial OTUs resulted in five additional bacterial taxa including Pseudomonas (OTU 10, 11, 12, and 13), Acinetobacter (OUT 14), Pantoea (OTU15), Erwinia (OTU 16) and Staphylococcus (OTU 17). Infection and diversity of bacterial communities across aphid species Diversity and prevalence of infection The bacterial communities were mainly composed of the primary symbiont B. aphidicola for all aphid species and mostly complemented by Re. insecticola for S. avenae and by Se. symbiotica for Si. maydis (Fig. 2). Figure 2. View largeDownload slide Summary of 16S rRNA gene sequencing-based taxonomic assignment for samples of cereal aphids. Each column represents the proportion of reads obtained from the sequence analysis of a single sample. Aphid species abbreviations: Dn: Diuraphis noxia, Rm: Rhopalosiphum maidis, Rp: Rhopalosiphum padi, Sa: Sitobion avenae and Sm: Sipha maydis. Figure 2. View largeDownload slide Summary of 16S rRNA gene sequencing-based taxonomic assignment for samples of cereal aphids. Each column represents the proportion of reads obtained from the sequence analysis of a single sample. Aphid species abbreviations: Dn: Diuraphis noxia, Rm: Rhopalosiphum maidis, Rp: Rhopalosiphum padi, Sa: Sitobion avenae and Sm: Sipha maydis. As shown in Fig. 3, the bacterial composition varied between aphid species. Regarding B. aphidicola, the large majority of the reads clustered into a single major OTU that was shared among all samples from the same aphid species, associated with one or three minor OTUs. The OTU1 was detected in R. padi and had 99% sequence identity with B. aphidicola previously described in this species (Munson et al.1991). The OTU2 was detected in S. avenae and matched to a sequence of B. aphidicola previously reported on this aphid species by Alkhedir et al. (2015). The OTU3 was detected only in Si. maydis and reported in Sipha genus by Nováková et al. (2013). The OTU4 was dominant in D. noxia and the OTU5 (with related minor OTU1) was detected in R. maidis. Figure 3. View largeDownload slide Relative abundance of bacterial taxa from Illumina sequencing of 16S rRNA amplicons, represented as a heat map based on the log-transformed values, with warm colors indicating higher and cold colors indicating lower abundance. Each color bar corresponding to one individual. Aphid species abbreviations: Dn: Diuraphis noxia, Rm: Rhopalosiphum maidis, Rp: Rhopalosiphum padi, Sa: Sitobion avenae and Sm: Sipha maydis. Figure 3. View largeDownload slide Relative abundance of bacterial taxa from Illumina sequencing of 16S rRNA amplicons, represented as a heat map based on the log-transformed values, with warm colors indicating higher and cold colors indicating lower abundance. Each color bar corresponding to one individual. Aphid species abbreviations: Dn: Diuraphis noxia, Rm: Rhopalosiphum maidis, Rp: Rhopalosiphum padi, Sa: Sitobion avenae and Sm: Sipha maydis. The prevalence of facultative endosymbionts varied between aphid species. Facultative endosymbionts were totally absent for D. noxia, R. maidis and R. padi, whereas a high prevalence of Re. insecticola and Se. symbiotica was observed in S. avenae (75.6%) and Si. maydis (100%), respectively. Hamiltonella defensa was present only in S. avenae with a low prevalence (6.7%). The co-occurrence of multiple facultative symbionts in the same sample was observed only twice in S. avenae and concerned the association between Re. insecticola and H. defensa (Table 3). Table 3. Prevalence of bacterial communities in cereal aphid populations collected from various host plants and localities. Types of bacteria Dn Rm Rp Sa Sm Total (n = 6) (n = 25) (n = 46) (n = 46) (n = 6) (n = 129) Primary symbiont Buchnera aphidicola 100 100 100 100 100 100 Secondary symbiont Serratia symbiotica 0 0 0 0 100 4.7 Regiella insecticola 0 0 0 75.6 0 27 Hamiltonella defensa 0 0 0 6.7 0 2.3 Secondary-free 100 100 97.8 22.2 0 67.2 co-infection 0 0 0 4.4 0 1.6 Other bacteria Erwinia 0 4 8.7 0 0 3.9 Pantoea 0 0 10.9 2.2 0 4.7 Pseudomonas 0 8 19.6 0 0 8.6 Acinetobacter 0 0 2.2 0 0 0.8 Staphylococcus 0 4 6.5 2.2 0 3.9 Other bacteria-free 100 88 71.7 95.6 100 85.9 Types of bacteria Dn Rm Rp Sa Sm Total (n = 6) (n = 25) (n = 46) (n = 46) (n = 6) (n = 129) Primary symbiont Buchnera aphidicola 100 100 100 100 100 100 Secondary symbiont Serratia symbiotica 0 0 0 0 100 4.7 Regiella insecticola 0 0 0 75.6 0 27 Hamiltonella defensa 0 0 0 6.7 0 2.3 Secondary-free 100 100 97.8 22.2 0 67.2 co-infection 0 0 0 4.4 0 1.6 Other bacteria Erwinia 0 4 8.7 0 0 3.9 Pantoea 0 0 10.9 2.2 0 4.7 Pseudomonas 0 8 19.6 0 0 8.6 Acinetobacter 0 0 2.2 0 0 0.8 Staphylococcus 0 4 6.5 2.2 0 3.9 Other bacteria-free 100 88 71.7 95.6 100 85.9 Aphid species abbreviations: Dn: Diuraphis noxia, Rm: Rhopalosiphum maidis, Rp: Rhopalosiphum padi, Sa: Sitobion avenae and Sm: Sipha maydis. Facultative-free: uninfected by facultative endosymbionts (only B. aphidicola). Co-infection: multiple infections by facultative endosymbionts in the same specimen. View Large Regarding extracellular bacteria, R. padi harbored a large diversity of bacterial species with intermediate prevalence (2.2%–19.6%). Rhopalosiphum maidis and S. avenae were characterized by low diversity and prevalence of these bacteria. Diuraphis noxia and Si. maydis were aposymbiotic for these bacteria (Table 3). Alpha diversity of bacterial communities Alpha diversity was computed for each sample after elimination of reads from B. aphidicola that were present in all samples. Using a multiple linear regression model, we found that the alpha diversity depended on altitude (P < 0.01) and aphid species (P = 0.05) as shown in Fig. 4. Aphids collected at low altitude presented bacterial communities with the highest alpha diversity. However, the effect of the host plant and other environmental parameters (bioclimate, temperature and precipitation) studied here was not significant (Fig. S2, Supporting Information). It is of note that our observational study design did not include any nested variable and that only weak-to-moderate correlations were found between the independent variables of the model (aphid species, host plant and environmental factors). All variables were therefore included in the multivariate model without any risk of multicollinearity problems. Figure 4. View largeDownload slide Alpha-diversity measurements according to altitude (A) and aphid species (B). Aphid species abbreviations: Dn: Diuraphis noxia, Rm: Rhopalosiphum maidis, Rp: Rhopalosiphum padi, Sa: Sitobion avenae and Sm: Sipha maydis. Figure 4. View largeDownload slide Alpha-diversity measurements according to altitude (A) and aphid species (B). Aphid species abbreviations: Dn: Diuraphis noxia, Rm: Rhopalosiphum maidis, Rp: Rhopalosiphum padi, Sa: Sitobion avenae and Sm: Sipha maydis. Differential abundance analysis The differential abundance analysis performed with the Deseq2 package identified significant associations between some taxa abundance and several factors including aphid species, altitude and host plant (Table S3, Supporting Information). Regarding the facultative symbionts, the abundance of Se. symbiotica was significantly higher (log2 fold-change = 13.496, adj. P-value < 0.0001) in Si. maydis than in S. avenae (taken as reference level). The abundance of Re. insecticola was significantly lower in R. padi, Si. maydis, D. noxia and R. maidis (log2 fold-change = –13.831, –10.860, –11.752, –13.642, respectively, all adj. P-value < 0.0001) than in S. avenae. Regarding other bacteria, abundance of Pseudomonas was significantly higher in Rhopalosiphum genus (R. padi and R. maidis) than in S. avenae (log2 fold-change = 3.396 and 2.078, respectively, adj. P-value < 0.0001 and 0.024, respectively). Similarly, Erwinia was more abundant in R. padi than in S. avenae (log2 fold-change = 3.895, adj. P-value = 0.010). Furthermore, the altitude reduced significantly the abundance of Pseudomonas (log2 fold-change = –2.552, adj. P-value < 0.0001). Concerning host plant, significantly higher abundance of Staphyloccocus was observed in T. turgidum than in Hordeum vulgare host plants (log2 fold-change = 2.485, adj. P-value < 0.0001). DISCUSSION Factors underlying changes in bacterial community There is mounting evidence that the microbiota of aphids is finely structured across geographical populations. The main environmental factors shaping this bacterial composition are considered to be host aphid species, host plants, climatic conditions and geographical location (Najar-Rodríguez et al.2009; Jones et al.2011; Brady et al.2013; Guidolin and Cônsoli 2017). Our results clearly showed that bacterial communities are mainly linked to host aphid species whereas no clear effect of the host plant was observed. This observation can be related to aphid sampling on three host plants within the same botanical family and is in line with previous observations based on populations of S. avenae collected on different Poaceae species in UK (Henry et al.2015). Surprisingly, factors such as bioclimate and precipitation level did not influence the diversity of bacterial communities although a highly variable composition in S. avenae endosymbionts was observed across different agroclimatic zones in Chile, suggesting that endosymbionts in this species are responding differentially to abiotic variables such as temperature and precipitations (Sepúlveda et al.2017). With regard to altitude, our results suggest that high altitudes act negatively on bacterial communities’ abundance and especially for the Pseudomonas (OTU 10 and 13). Further works at large-scale are therefore required to identify the composition of bacterial communities associated to aphids and their frequency in other regions of the world. Diversity and composition of the cereal aphid microbiota 16S rRNA amplicon-based Illumina sequencing enabled us to identify 10 bacterial genera in five cereal aphid species. Although our analyses covered a large number of samples collected from different ecoclimatic regions of Morocco (Fig. S1, Supporting Information), the global diversity of bacterial communities was relatively low with the number of OTUs ranging between 3 and 8 within each sample. Similar observations were reported in previous studies, i.e. a number of OTUs per sample ranging from 3 to 11, depicting the microbial communities associated with families of Hemiptera (Najar-Rodríguez et al.2009; Jing et al.2014; Gauthier et al.2015). In practice, each sample analyzed contained three aphid individuals from the same colony. Under these conditions, a risk of underestimation is therefore possible. In fact, if only one individual is contaminated, the amount of DNA in the bacteria contained is diluted in the total DNA of the three aphids and there is a risk of falling below a threshold of detectability. However, this risk is low given the performance of sequencing technique. Furthermore, individuals from an aphid colony are generally the parthenogenetic progenies of a single female and, as aphid endosymbiotic bacteria are usually maternally transmitted (Michalik et al.2014), it is therefore likely that all the individuals from a given colony have the same endosymbionts. However, it is still possible that some of the colonies we sampled were founded by different females. Under these conditions, the prevalence recorded in our work may be underestimated and should be taken with care as a first estimation of cereal aphid's microbiome diversity. Strains with distinctive 16S haplotypes of the obligate symbiont B. aphidicola were identified, the more divergent being found in Si. maydis. Slightly divergent B. aphidicola (differing by 9–35 bp on a ∼464 bp sequence) were found in a single aphid colony. These results provide a strong indication of intraspecific divergence in B. aphidicola strains. Such divergence might be a consequence of Buchnera polyploidy, as evidenced by the 16S rRNA copy number variation (Komaki and Ishikawa 1999). Alternatively, a clone from a single colony may contain Buchnera strains with different haplotypes. Co-infection with multiple B. aphidicola strains was also recently reported in several aphid genera (Jones et al.2011; Jousselin et al.2016). Irrespective of these observations, little is known about the phenotypic and fitness consequences of co-infections with multiple strains from the same heritable symbiont species. This underestimated diversity at the host's intraspecific level could have significant consequences in terms of ecology and the evolutionary trajectory of host insects. For instance, distinct strains of B. aphidicola were found to exert different effects on host adaptations to temperature regimes (Wernegreen 2012). It has remained unclear exactly how Buchnera strains sharing the same host and evolving in parallel affect their hosts. Strain variation is more extensively studied in facultative symbionts, where symbiont divergence may result in phenotypic differences that can greatly affect adaptation of aphid hosts to their environment, such as to their host plant or resistance to parasites (Oliver et al.2003; Oliver, Moran and Hunter 2005; Ferrari, Scarborough and Godfray 2007). Regarding the facultative endosymbiont composition, only three facultative endosymbionts (i.e. Re. insecticola, Se. symbiotica and H. defensa) were identified in cereal aphids. This seems very little compared to A. pisum that harbors nine facultative endosymbionts (Russell et al.2013). In addition to the co-infection of endosymbionts belonging to the same species, co-infections by multiple heritable endosymbiont species have also been documented. Studies based on the pea aphid model A. pisum have shown that the same host can harbor up to four facultative endosymbionts (Ferrari et al.2012), with a prevalence reaching 25% (Russell et al.2013). In our study, a low prevalence of co-infection was recorded (1.6% of all samples) and mainly involved the facultative endosymbionts Re. insecticola and H. defensa. A number of key assumptions could explain these differences in terms of co-infection occurrence in field populations. According to Brady et al. (2013), the reproductive mode may significantly impact the frequency of co-infection in aphids. Indeed, the sexual phase of reproduction in A. pisum is considered the main route of horizontal transmission of facultative endosymbionts and may contribute to a high prevalence of co-infection (Moran and Dunbar 2006). Degree of polyphagy is another factor that could influence the diversity of symbionts in insects (Ferrari, Scarborough and Godfray 2007; Jaenike et al.2007; Brady et al.2013). Indeed, polyphagous species are expected to face more nutritional challenges and are thus expected to host a higher diversity of endosymbionts compared to oligophagous species. The scarcity of co-infection with facultative endosymbionts could also suggest a potential trade-off for aphid hosts possibly fueled by host-harming competition between those bacteria (Russell et al.2013). Structure of the bacterial community in relation to host aphid species We have made several key observations on the structuring of bacterial communities with regard to host aphid species. First, facultative symbionts were absent in D. noxia, R. padi and R. maidis, which is in line with previous data (Sandström et al.2001; Henry et al.2015). Conversely, a prevalence of 75.6% was observed for Re. insecticola in S. avenae, which contradicts previous observations reporting a low prevalence of this symbiont in the populations from UK (Alkhedir, Karlovsky and Vidal 2013; Łukasik et al.2013a; Sepúlveda et al.2017). Regiella insecticola has the capacity to confer resistance to parasitoids and fungal pathogens (Scarborough, Ferrari and Godfray 2005; Vorburger, Gehrer and Rodriguez 2010; Parker et al.2013), to enhance reproduction (Leonardo and Mondor 2006) or to play a role in the specialization and exploitation of host plants. The high prevalence of Re. insecticola observed in this study could probably result from its potential protective effect against the parasitoid Aphidius ervi (Hansen, Vorburger and Moran 2012). Indeed, this parasitoid species is massively present at the end of April, i.e. during our sampling period (Fahkour, personal observation). It further coincides with the highest parasitoid activity, which is the main biological control agent against S. avenae in Morocco (Sekkat and El-Bouhssini 1992). Increased parasitoid attack rates could thus lead to a sharp increase in prevalence of some defensive facultative endosymbionts in aphid populations (Oliver et al.2008). In this study, S. avenae was infected by H. defensa with low prevalence (6.7%). Although H. defensa is reported to protect aphids against parasitoids (Oliver et al. 2003; Oliver, Moran and Hunter 2005; Vorburger 2014), its specific effects on S. avenae are still unclear. The presence and the type of the APSE bacteriophage in H. defensa genome play a central role in the level of protection against parasitoids, as it recently demonstrated thanks to in vitro cultivations of the bacteria (Brandt et al.2017). Deeper characterizations of the strain occurring in S. avenae are needed to test for potential host fitness effects. The prevalence of Se. symbiotica in Si. maydis was surprisingly high by reaching 100%. While these results are based only on six colonies, these ones were geographically distant from each other (Fig. 1). Further, this result has been confirmed with additional samples of Si. maydis (n = 21) that were individually assessed by PCR aimed at detecting Se. symbiotica (unpublished results). Phylogenetic analyses reveal that the Se. symbiotica strains found in Si. maydis (SSm) belong to a different haplotype than the strain found in A. pisum (SAp) (Fig. S3, Supporting Information). The bootstrap-based phylogenetic placement of Ssm shows that it is grouped in the same clade as the co-obligate Se. symbiotica from Cinara tujafilina. Such high prevalence suggests a potential nutritional role and co-obligate function of this strain in Si. maydis, where Se. symbiotica is clearly located in secondary bacteriocytes (Fakhour et al., in preparation). Interestingly, the B. aphidicola strain found in Si. maydis is phylogenetically distant from Buchnera strains in other cereal aphid species whilst being phylogenetically closer to Buchnera strains belonging to the genus Cinara (Fig. S4, Supporting Information). Further investigation and deeper phylogenetic characterization of Ssm strains based on multilocus sequence typing are therefore needed to decipher the potential nutritional role of this strain and its obligate symbiotic status in Si. maydis. Serratia symbiotica is generally associated with tolerance to heat stress in A. pisum (Montllor, Maxmen and Purcell 2002; Russell and Moran 2006), and Se. symbiotica infection is common in pea aphid from arid countries (Chen and Purcell 1997; Henry et al.2013). Considering the prospected aphid populations from arid regions of Morocco, the absence of Se. symbiotica from aphid species other than Si. maydis is quite surprising. In conclusion, cereal aphids harbor relatively small endosymbiotic communities, irrespective of the diverse geoclimatic conditions of Morocco. However, the structure of these bacterial communities varied considerably among aphid species. Aphids and their bacterial associates form a community integrated into a dynamic ecosystem that is subjected to various selection pressures and is the outcome of a long-standing association and potentially coevolution. In this context, seasonal variations in the frequencies of heritable defensive bacteria from natural populations across host plants and geographic regions were reported by Smith et al. (2015). Further work is therefore required to determine whether the geographical and temporal differences detected persist across seasons and years. In addition, aphids may acquire extracellular bacteria as has been demonstrated for aphid colonies living in close contact with the rhizosphere. Assessing the hidden microbial diversity and its effects on local host–endosymbiont adaptation are of great importance to better understand symbiont-mediated adaptation of aphids to local conditions, as well as for the practical application of these findings in novel insect pest control programs. DATA ACCESSIBILITY European Nucleotide Archive (ENA) accession number for NGS sequences generated for the 129 aphid samples reported in this paper is PRJEB23277. The 16S rRNA gene sequences data of the dominant bacterial taxa of cereal aphids were deposited in the NCBI database under the accession numbers (Table S2, Supporting information). SUPPLEMENTARY DATA Supplementary data are available at FEMSEC online. Acknowledgements We are grateful to M. Aqim and E.M. Chafaie for their great efforts in sampling aphids from Morocco. We thank A. Sekkat for aphid identification and the Pr C. Bragard for lab technical facilities. We thank Dr L. Karim and W. Coppieters from the Platform GIGA, University of Liege for performing Illumina MiSeq sequencing. We thank I. Pons for her contribution in the phylogenetic analysis and K. Andich for extrapolation of climatic factors. We thank B. Visser and G. Le Goff for English corrections. We also thank the reviewers for valuable suggestions to improve this paper. We are thankful to the Director, INRA from Morocco for the support and facilities. This publication is 396 BRC of the Biodiversity Research Centre (Catholic University of Louvain). AUTHOR CONTRIBUTIONS SF, TH and VF designed the study. SF sampled aphids, extracted the DNA and performed the first stage of PCR. JA, SF and JLG analyzed the data. SF interpreted the results. SF and FR wrote the paper. All authors revised and accepted the final version of the manuscript. FUNDING This work was supported by the Merit Scholarship Program for High Technology from the Islamic Development Bank [IBD File No. 51/MOR/P33-600029718]. Conflict of interest. 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FEMS Microbiology Ecology – Oxford University Press
Published: Mar 1, 2018
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