The Mallophaga Family ______________ Are All Ectoparasites of Birds.

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Research Article

The microbiota of hematophagous ectoparasites nerveless from migratory birds

• Paola Modesto,
• Francesca Rizzo,
• Alessandra Cravero,
• Irena Jurman,
• Stefano Costa,
• Mauro Giammarino,
• Maria Lucia Mandola,
• Mariella Goria,
• Slobodanka Radovic,
• Federica Cattonaro,
• Pier Luigi Acutis,
• Simone Peletto

The microbiota of hematophagous ectoparasites nerveless from migratory birds

• Francesco Cerutti,
• Paola Modesto,
• Francesca Rizzo,
• Alessandra Cravero,
• Irena Jurman,
• Stefano Costa,
• Mauro Giammarino,
• Maria Lucia Mandola,
• Mariella Goria,
• Slobodanka Radovic

x

• Published: August 27, 2018
• https://doi.org/10.1371/journal.pone.0202270

Figures

Abstract

Arthropod vectors are responsible for the transmission of human pathogens worldwide. Several arthropod species are bird ectoparasites, however, no written report to date has characterized their microbiota equally a whole. Nosotros sampled hematophagous ectoparasites that feed on migratory birds and performed 16S rRNA gene metabarcoding to characterize their microbial community. A total of 194 ectoparasites were collected from 115 avian hosts and classified into three groups: a) Hippoboscidae diptera; b) ticks; c) other arthropods. Metabarcoding showed that endosymbionts were the most abundant genera of the microbial community, including Wolbachia for Hippoboscidae diptera, Candidatus Midichloria for ticks, Wolbachia and Arsenophonus for the other arthropod grouping. Genera including pathogenic species were: Rickettsia, Borrelia, Coxiella, Francisella, Bartonella, Anaplasma. Co-infection with Borrelia-Rickettsia and Anaplasma-Rickettsia was also observed. A global overview of the microbiota of ectoparasites sampled from migratory birds was obtained with the use of 16S rRNA gene metabarcoding. A novel finding is the get-go identification of Rickettsia in the common swift louse fly, Crataerina pallida. Given their possible interaction with pathogenic viruses and bacteria, the presence of endosymbionts in arthropods claim attention. Finally, molecular characterization of genera, including both pathogenic and symbiont species, plays a pivotal part in the design of targeted molecular diagnostics.

Commendation: Cerutti F, Modesto P, Rizzo F, Cravero A, Jurman I, Costa S, et al. (2018) The microbiota of hematophagous ectoparasites collected from migratory birds. PLoS ONE 13(8): e0202270. https://doi.org/ten.1371/periodical.pone.0202270

Editor: Brian Stevenson, University of Kentucky College of Medicine, UNITED STATES

Received: November vii, 2017; Accustomed: July 31, 2018; Published: August 27, 2018

Copyright: © 2018 Cerutti et al. This is an open admission article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted apply, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: Relevant data can be plant in the paper and its Supporting Information files. Sequencing data can be accessed at https://www.ncbi.nlm.nih.gov/ under accession number SRP113690 or direct at https://world wide web.ncbi.nlm.nih.gov/Traces/study/?acc=SRP113690.

Funding: This work was supported by the Italian Ministry of Wellness [Ricerca Corrente 2012 IZS PLV 16/12 RC]. Irena Jurman, Slobodanka Radovic and Federica Cattonaro are employed by IGA technology services. IGA applied science services provided back up in the form of salaries for authors IJ, SR and FC, but did not have any boosted function in the study pattern, data collection and analysis, conclusion to publish, or preparation of the manuscript. The specific roles of these authors are articulated in the 'writer contributions' section.

Competing interests: Nosotros have the following interests: Irena Jurman, Slobodanka Radovic and Federica Cattonaro are employed by IGA technology services. Stefano Costa is employed by Laboratorio Chimico Camera Commercio Torino. There are no patents, products in development or marketed products to declare. This does not alter our adherence to all the PLOS One policies on sharing data and materials.

Introduction

Arthropod vectors are responsible of numerous diseases (named vector-borne diseases) worldwide [ane]. Mosquitoes, ticks, Phlebotominae and Simuliidae flies are ectoparasites that tin can transmit viruses (e.g., Dengue virus, Yellow fever virus, Due west Nile virus (WNV), and Zika virus), bacteria (e.g., Borrelia spp., Rickettsia spp., Francisella tularensis, Coxiella burnetii), and parasites (e.g., malaria Plasmodium spp., trypanosomes, Leishmania spp.) [one]. The 2016 Zika virus pandemic is only the about recent example of a global vector-borne disease emergency among the many other pathogens for which there is an epidemic trend [2]. For example, the hard tick Ixodes ricinus, present throughout Europe, is involved in the transmission of a diverseness of pathogens of medical and veterinary importance including Borrelia burgdorferi south.l., tick-borne encephalitis virus, Anaplasma phagocytophilum, Francisella tularensis, Rickettsia helvetica and Rickettsia monacensis, Babesia divergens and Babesia microti, Louping ill virus, and Tribec virus [3].

Some of the arthropods responsible for disease transmission share their environment with birds. Mosquitoes belonging to Culex are, in fact, mainly ornithophilic and are the main vectors of WNV and Usutu virus. Moreover, birds physically carrying arthropods (such as ticks or mites) feeding on them can introduce novel species to Europe, as recently recorded for the U.Grand. [4–6].

Attributable to its geographical location, the Italian peninsula is crossed past migratory routes from North and sub-Saharan Africa. To our knowledge, no data accept been published on the whole microbiota of ectoparasites collected straight from migratory birds, though a few studies have described the presence and prevalence of specific genera of bacteria in ticks collected from birds or their nests [7, 8]. Since these ectoparasitic arthropods may carry pathogens, it may exist relevant to study their microbial communities. Other than bacteria of public health interest, the microbiota of arthropods is circuitous. It has been described in ticks and mosquitoes [9–12] and the role of symbionts in influencing the microbial limerick has been highlighted mainly in its interaction with pathogens. Symbionts like Wolbachia can influence arthropod reproduction, including male-killing, parthenogenesis, feminization, and embryonic mortality [13]. Furthermore, they may evolve the necessary adaptations to parasitize vertebrate cells, every bit recently demonstrated that the intracellular bacterium Coxiella burnetii evolved from a maternally-inherited endosymbiont of ticks [fourteen]. Adaptation may as well occur in the contrary direction, every bit in the case of the Francisella-like endosymbiont that evolved from Francisella tularensis [xv].

For this report, we collected ectoparasites feeding on migratory birds during ringing sessions and then candy the arthropod samples for 16S rRNA gene metabarcoding to characterize their microbial community. Special care was paid to identify the genera usually associated with pathogens. The samples reporting these leaner were farther tested with genus-specific or species-specific molecular assays.

Materials and methods

Sample collection

The ectoparasites were collected from birds during ringing sessions from November 2012 to October 2014. A full of 35 sessions were carried out at 14 dissimilar sites in five regions (Piedmont, n = 105; Lombardy, due north = 5; Sicily, n = four; Latium, n = 1; Liguria, n = 1; S1 Fig). A total of 194 ectoparasites were collected from 115 birds, divided into 120 pools by parasite type [a) Hippoboscidae diptera; b) ticks; c) other arthropods], host species, sampling site, date, and location. The species included in the other-arthropods group were: Anatoecus dentatus, Anaticola, Lucilia caesar, Colpocephalum turbinatum, Anystis, and Aphidiinae spp. Details on host species are reported in S1 Tabular array.

The birds were defenseless with mist nets according to the Euring Ringing Organization and retrieved by authorized personnel. Afterward capture the birds were ringed with a metallic ring on the correct leg. In Italy, bird leg rings are supplied by the Establish for Environmental Protection and Inquiry (ISPRA) and they bear a unique, permanent code identifying any ringed bird for life. The birds were and so identified by species, sexed, and assigned to age categories according to plumage. They were released afterwards ectoparasite collection by veterinarians with ISPRA authorization. Existence a not-invasive procedure, no special permission was needed for drove. Parasites from common swifts, mainly Hippoboscidae diptera, were nerveless either direct from the birds or from their nests in dedicated stations.

To preserve nucleic acids and obtain skillful quality material for metabarcoding, live parasites were stocked in RNAlater^TM stabilization solution (Invitrogen, Carlsbad, CA, USA) and stored at -lxxx°C until processed. The parasites collected from each bird were pooled together in a single vial, except for ii birds (Apus apus), for which the parasites were stored separately for preliminary evaluation of RNA integrity. Data on sampling site location, bird age, sexual practice, and wellness status were collected and entered in a database.

RNA extraction

As the rationale of the study was to describe the living leaner (i.e., synthesizing RNA), we analyzed the total RNA to characterize only the agile microbiota and to remove bias from the DNA carried over from expressionless prokaryotic cells. RNA purification was performed with TRIzol™ (Invitrogen) in combination with a Nucleospin miRNA kit (Macherey-Nagel, Düren, Germany) following the manufacturer's protocol for RNA purification of small and large RNA in 2 fractions. The large and modest RNA fractions were stored at -80°C for further analysis.

Total RNA concentration and purity was estimated using a spectrophotometer for small volumes (Vivaspec, Sartorius, Göttingen, Germany) and a fluorometer (Qubit two.0, Thermo Fisher Scientific, Waltham, MA, USA). The quality of total RNA was evaluated using a 2100 BioAnalyzer and an RNA 6000 Nano Kit (Agilent Technologies, Santa Clara, CA, USA). Though it was non possible to calculate the RIN (RNA Integrity Number) values [16], since the 28S rRNA subunit of many arthropods contains 2 hydrogen-bonded fragments that dissociate and co-drift with the 18S subunit [17], the graph showed a 28S/18S precipitous peak associated with a apartment baseline that indicated the absence of degradation.

Reverse transcription and arthropod species identification

Full RNA was contrary transcribed using a High-Chapters cDNA Reverse Transcription Kit (Thermo Fisher Scientific) with 7 μl RNA as input and then stored at -20°C until processed. Vector species was determined by fractional distension and sequencing of the cytochrome c oxidase I (COI) cistron, equally described by Hebert and colleagues [eighteen]. Briefly, the reaction mix was equanimous of 12.v μl SuperMix PCR-UDG 2X (qPCR ProbesMaster, Jena Bioscience, Jena, Germany), 0.38 μl primer LC01490 20 μM, 0.38 μl primer HC02198 20 μM, xi μl Water, 0.75 μl cDNA, for a total volume of xx μl. The thermal profile was: fifty°C x 2 1000; 95°C x two m; 40 cycles {94°C ten 30 s, 49°C 10 thirty s, 72°C x 1 m}; 72°C 10 v m.

Successful amplification was verified using Eastward-Gel® precast agarose gels at ii% (Thermo Fisher Scientific). Amplicons were then purified with a EUROGOLD Cycle-Pure kit (Euroclone, Pero, MI, Italy). The cycling reaction was performed with a BigDye® Terminator v1.1 bike sequencing kit (Thermo Fisher Scientific): 2 μl BigDye® Terminator v1.i ready reaction mix, ane μl 5X sequencing buffer, 0.32 μl primer 100 μM, 4.68 μl H2O, 2 μl purified amplicon. The thermal profile was: 96°C x i m; 25 cycles at 96°C 10 1 m, 50°C x 5 s, 60°C x 4 m. The reaction was purified with a GE Healthcare Illustra™ AutoSeq G-50 columns kit (GE Healthcare, Chicago, IL, USA) to remove dye terminators, and then submitted to sequencing on an Applied Biosystems AbiPrism 3130 (Foster Urban center, CA, USA).

Chromatograms were analyzed with Sequencing Analysis v5.2 software (Thermo Fisher Scientific) for the base telephone call and with FinchTV (Geospiza, Inc, Seattle, WA, The states) for manus editing. The obtained nucleotide sequences were used equally query in a Blastn search on the GenBank nt database and in the Assuming database (Barcoding Of Life Database, world wide web.boldsystems.org).

16S metabarcoding

The 16S rRNA cistron metabarcoding of 116 out of 120 samples was performed following the protocol suggested past Illumina (four samples were discarded as they were non of adequate quality for sequencing). Briefly, 22.5 ng of cDNA was used every bit input for the first PCR using 16S amplicon PCR forward and reverse primers, amplifying V3-V4 regions of the 16S rDNA. Subsequently purification and 2nd (alphabetize) PCR with a Nextera XT Index kit (Illumina, San Diego, CA, United states of america), the libraries were normalized according to fragment length and dsDNA molarity. The samples were pooled and processed in iv sessions on a MiSeq platform (Illumina) using a MiSeq reagent kit v3-600 for 2x300 paired-end sequencing at the IGA Technology Services facility. The datasets generated and analyzed for this study are available in the BioProject database, with SubmissionID: SUB2898018 and BioProject ID: PRJNA396024.

Bioinformatic and statistical analyses

A starting time level analysis for all samples was achieved with MiSeq Reporter Metagenomics Workflow (MSR, Illumina) to gain an overview of the microbial customs for each pool. The dataset was then analyzed post-obit DADA2 workflow inside the R framework, including quality check, error rate estimation, forrad/reverse reads merge, bubble removal, ribosomal sequence variants (RSVs, equivalent to OTUs) decision, and taxa assignment to the GreenGenes gg_13_8_train_set_97, RDP Training Ready fourteen and SILVA version 128 reference databases for comparison [19–23]. Since SILVA performed better than the other two in classifying arthropod bacterial symbionts to appropriate taxa, only these results are presented. Data were also analyzed with the QIIME v.1.ix.1 pipeline, and the results were largely consequent with those obtained with DADA2.

Alpha and beta diversities were estimated with the pyhloseq and vegan packages and visualized with the ggplot2 package, and differential expression was assessed with DeSeq2 [24–27]. Alpha diversity was estimated based on the observed species and Shannon alphabetize using the whole dataset after removing RSVs unassigned or assigned to Eukaryota. Beta multifariousness was estimated based on evenly sampled Bray-Curtis altitude after filtering the depression-frequency RSVs, pruning the samples with a sample size less than i,800 and rarefaction to sample size of 1,800, where sample size was the number of individuals observed for each sample. Merely information from DADA2 analysis using the SILVA database are presented in Results.

Molecular diagnostics for potential pathogen confirmation

To confirm the presence of the prokariotic genera identified by 16S rRNA metabarcoding, the pools were tested using a genus-specific or species-specific PCR for each of the potential pathogens detected by the MiSeq Reporter Metagenomics Workflow. The molecular tests included the post-obit genera: Rickettsia spp., Anaplasma spp., Borrelia spp., Coxiella spp., Francisella spp., and Bartonella spp. For all PCR assays, amplicons were purified and submitted to Sanger sequencing as described earlier for the PCR targeting the COI gene.

Two different PCR assays to confirm and characterize Rickettsia were used: one targeting the citrate synthase gene, according to Regnery and colleagues [28], and the other targeting the 16S rRNA gene, according to Sprong and colleagues [29]. A PCR amplifying the partial 16S rRNA factor was used to identify A. phagocytophilum according to Stuen and colleagues [30]. Ii dissimilar approaches were applied to identify Borrelia burgdorferi south. l. Existent-time PCR targeting a tract of the 23S rRNA gene, highly conserved in all Borrelia species, was used to confirm positivity, as described in Courtney and colleagues [31]. An cease-indicate PCR targeting a fragment of the flagellin gene, specific for the Borrelia burgdorferi s. l. group, was then used to make up one's mind whether the detected strain belonged to the causative agents of Lyme borreliosis [32]. The genomic group of samples positive for Borrelia burgdorferi southward. l. was then identified by sequencing. A qualitative PCR targeting the IS1111 repetitive transposon-similar region of Coxiella burnetii was performed to confirm Coxiella spp., as recommended by the Manual of Diagnostic Tests and Vaccines for Terrestrial Animals [33, 34]. Francisella spp. was investigated using a real-fourth dimension PCR TaqMan® Francisella tularensis detection kit (Applied Biosystems) that targets the Tul4 and fopA genes. Francisella characterization was performed by targeting the 16S rRNA gene, according to Forsman and colleagues [35].

Results

Host and parasite species

A total of 115 bird hosts were included. S1 Table presents the species and the number of samples collected. Hosts were classified based on their migratory behavior as: resident, curt-distance, mid-altitude (North Africa) or long-distance (trans-Sahara) migration. A total of 194 parasites were collected and categorized into three groups based on the blazon of arthropod: Hippoboscidae diptera (n = 51, puddle (n) = 49), ticks (n = 114, pool (north) = lx), other arthropods (OA, n = 29, pool (n) = 7). Hippoboscidae diptera were collected from common swifts (Apus apus) and classified past barcoding as Crataerina pallida. Ane sample of Hippoboscidae was collected from a goldcrest (Regulus regulus) and was classified as Ornithomya fringillina. The tick group included species of the genera Ixodes, Hyalomma, Ambylomma, and Haemaphysalis. The OA included lice (Mallophaga: Colpocephalum turbinatum, Anatoecus dentatus, and unidentified species), blowflies (Diptera: Calliphoridae: Lucilia caesar), mites (Trombidiformes: Anystis), the parasitoid wasps (Hymenoptera: Braconidae: Aphidiinae). A detailed list of ectoparasite species and number of sampled individuals and pools is given in S2 Tabular array.

16S metabarcoding

A total of 116 pools were candy for V3-V4 16S rRNA gene amplification and massive parallel sequencing on an Illumina MiSeq platform, generating too a taxonomic report with MiSeq Reporter Software. The total amount of reads generated was 45,286,016 (median = 323,508, Q1 = 203,740, Q3 = 510,136); after quality filtering 24,012,404 reads per pair (median = 82,992, Q1 = 48,206, Q3 = 143,460, with read length uniformed to 230 bp) were obtained. Details on raw and filtered read numbers for each sample are reported in S3 Table. The resulting 257,298 dereplicated non-chimeric sequences were assigned to 2,257 RSVs, belonging to Bacteria and Eukaryota domains. Taxa assigned to Eukaryota or unassigned were removed, reducing the concluding number of RSVs to two,184, classified in 23 different phyla. The most abundant phyla in the whole dataset were the Proteobacteria (90.72%) and the Firmicutes (5.44%). The about mutual genera for the whole dataset are reported in Tabular array i, and the taxa with relative affluence >1% are reported past group in Table 2. Fig i presents a graphical overview of the genera identified in each sample. The most arable taxonomic groups of the bacterial composition at a lower taxonomical scale included symbionts similar Wolbachia, Arsenophonus, and Candidatus Midichloria mitochondrii.

To better visualize the distribution of the symbiont genera in the Hippoboscidae diptera, a bar plot of the relative abundance within the family is reported in S2 Fig. Due to the large number of genera detected, Rickettsiales from ticks are reported in a bar plot (S3 Fig). To ameliorate stand for the diversity of the symbionts within parasite species, the number of RSVs belonging to each genus are summarized in Tabular array iii. According to the DADA2 developers, this algorithm in able to discover true biological sequence variants that might be considered different bacterial strains. The composition in RSVs of the major symbiont genera of Hippoboscidae diptera and ticks are reported in S4 Fig and S5 Fig.

Bioinformatic and statistical analysis

The reports generated by the integrated pipeline of the Miseq Reporter were analyzed. Based on these results, the samples were considered positive or negative for the detected potentially pathogenic genera. Tabular array 4 reports the number of samples in which the MSR institute the respective genus (MSR Hits). The microbiota of the three groups of ectoparasites differed in microbial composition by both abundance and represented taxa. Box-plots illustrating alpha diversity are reported in Fig 2. The Shannon index showed no statistically significant difference betwixt the groups (box-plot Fig 2). At that place was a statistically significant difference in the number of species for the three groups. The box-plot represents the low number of species in the Hipposboscidae diptera grouping as compared to the other 2 groups. The master coordinates analysis based on the Bray-Curtis distance highlighted a difference in microbial limerick in the microbiota of the Hipposboscidae diptera every bit compared to that of the ticks and the OA groups (PERMANOVA test implemented in the adonis function in vegan) (Fig iii).

Tabular array 4. Hits and PCR positivity to genera including known pathogen species.

Hits (OTUs matching a given genus) were obtained by MiSeq Reporter (MSR) assay. Prevalence was calculated on 116 samples. The 95% confidence interval (CI) of the prevalence is reported in brackets.

https://doi.org/10.1371/journal.pone.0202270.t004

Molecular diagnostics for potential pathogen confirmation

As summarized in Table 4, Rickettsia and Ehrlichia were highly represented amidst the samples, with more than than fourscore% of the samples having reads corresponding to these two genera. The diagnostic PCR for Rickettsia spp. confirmed only 47 positive samples (42% of hits, 40.5% of full samples), farther characterized as R. aeschlimannii, R. helvetica, and R. monacensis. Some of the sequences were similar to unclassified endosymbionts, 6 of which were were close to R. bellii, a species institute simply in the Americas (U.s., Brazil, Argentina, Costa rica, Colombia, El Salvador, Republic of peru) [36–42]. Equally described for C. burnetii [43], identification of Rickettsia endosymbionts by means of a PCR used for pathogen detection in routine work shows that these species may interfere with the correct diagnosis of pathogenic rickettsial species.

Borrelia spp. were confirmed in 10 samples, four of which were farther confirmed by the PCR specific for Borrelia burgdorferi s.l. and classified equally B. valaisiana. The two samples positive for Francisella spp. were Francisella-like endosymbionts, while the two Anaplasma positive samples belonged to A. phagocytophilum. Ehrlichia required a dissimilar approach, since the MSR identified E. ovina in 98 samples, a species poorly described in the literature. On the ground of this unexpectedly loftier prevalence, and in contrast to only 3 sequences registered in the NCBI database, we suspected a misclassification issue, so we randomly chose ane sample and retrieved the reads assigned to this species. A Boom search confronting the NCBI 16S prokariotic rRNA database was performed and the results were then plotted in MEtaGenome ANalyzer. The output is reported in S6 Fig The reads were classified every bit Anaplasmataceae, and at a lower taxonomic level equally Candidatus Midichloria mitocondrii, Anaplasma spp., and Wolbachia spp. For this reason, the samples were not tested for Ehrlichia spp.

Among the PCR-confirmed samples, the post-obit co-infections were observed: Borrelia-Rickettsia (northward = 9), two of which occurred in individual samples, and Anaplasma-Rickettsia (n = 2). Considering only the ticks, the prevalence of confirmed Rickettsia spp. in the tick-only grouping was threescore.32% (95% CI: 47.98–71.47), 15.87% (95% CI 8.86–26.81) for Borrelia spp., and 18.37% (95% CI 9.98–31.36) for Ixodes. Rickettsia spp. was present in numerous samples and detected in parasites nerveless from resident (n = 2), short-distance (n = 32), mid-distance (due north = 2), and long-altitude (north = eleven) migratory birds. Borrelia spp. was detected just in ticks from brusk- and mid-distance migratory birds.

Discussion

With this report we wanted to draw the microbiota of ectoparasites nerveless from migratory birds since they constitute a route of introduction for exotic vector-borne diseases. The parasites were divided into three groups based on taxonomical features and sample size: Hippoboscidae diptera, ticks, and other arthropods. The microbiota of the Hippoboscidae diptera was equanimous of a express number of species, as expressed past the depression value of the observed species. Considering the evenness (Shannon index), the diversity was comparable to the tick and the OA groups. The depression number of species may exist explained past the predominance of symbiont species among the virtually abundant genera observed, such as Wolbachia, Arsenophonus, and Sodalis (Sodalis endosymbionts were likewise detected in Craterina melbae) [44–47]. The deviation in microbial composition past number and taxonomy of the RSVs in the three groups is supported past the pregnant departure in the alpha and beta diversity, suggesting that the bacterial communities are heavily influenced by the parasite they live with. Briefly, the almost abundant symbionts were Wolbachia, Rickettsia, Arsenophonus, and C. Midichloria. They were closely associated with the type of arthopod: Hippoboscidae were mainly colonized by Wolbachia and Arsenophonus and ticks by Rickettsia and C. Midichloria.

Regarding the distribution of the primary genera in the Hippoboscidae, the microbial population of all only three samples was almost totally composed of Wolbachia. The three Wolbachia-free samples were totally colonized by Arsenophonus, while Sodalis was present merely together with other symbionts. Merely in three samples Wolbachia was the unique genus, for a total of six individuals with a unmarried symbiont. Although the relative abundance is based on the family, the majority of the Hippoboscidae was colonized by at least two symbiont genera (S2 Fig).

Wolbachia strains seemed to be closely connected to host species (S4 Fig); C. pallida was mainly colonized by ane variant and O. fringillina by another. In dissimilarity, Arsenophonus in C. pallida had a slight diversity (with RSVs similar by 99.thirty–99.53%), while in O. fringillina it was nowadays simply as one RSV (like to other Arsenophonus symbionts of Ornithomya species). The loftier homogeneity of Wolbachia suggests that it may be an obligate symbiont vertically inherited by maternal lineage. Differently, the multifariousness of Arsenophonus within samples suggests that information technology may take been transmitted horizontally or by other ways. The high presence of Wolbachia ascertain this genus as the predominant symbiont. While it might be an obligate symbiont within C. pallida, the presence of other genera suggests that they still play an of import office in the survival of Hippoboscidae, only further data are needed.

To our noesis, this study is the first identification of Rickettsia bellii and R. monacensis in the Hippoboscidae C. pallida. Strains of R. bellii take been reported only for the Americas; like strains take been detected in Commonwealth of australia, Thailand, Réunion Isle, and Japan [44–47]. Our report is the start identification of R. bellii in Italy and Europe. This finding raises the question every bit to whether C. pallida behaves as an accidental vector for rickettsiosis or, if not competent for manual, whether information technology might play a role as a sentinel parasite for the spread of arthropod-borne pathogens.

In ticks, the endosymbiont Candidatus Midichloria deemed for half of the RSV abundance in the samples, followed by Rickettsia spp. When Rickettsia spp. was nowadays, it had the highest prevalence in almost all samples; simply in one sample, Rickettsia was present but the predominant genus was Midichloria. As reported elsewhere, Wolbachia symbionts in ticks are rare [48]. Unlike a recent report on ticks in French republic, our report noted no relevant presence of Acinetobacter, merely we did detect co-infection with pathogens and symbionts in our samples [49]. In the samples with merely one tick, we observed co-infection mainly betwixt Rickettsia and Midichloria; besides Wolbachia, Rickettsiella, Neoehrlichia, and Spiroplasma were present together with other symbionts. Candidatus Midichloria was present mainly in Ixodes ricinus ticks, where it was represented past a unique variant. Unfortunately, the sample size was too modest to make further observations for other species like I. arboricola and Hyalomma spp.

Candidatus Midichloria was first described in 2006 as an endosymbiont of Ixodes ricinus, and was later also detected in other hard ticks (Ixodidae) in Italy [50–51]. The detection of circulating DNA and the presence of antibodies against an antigen confronting G. mitochondrii in humans and mammals suggest that it might represent a novel grouping of vector-borne agents [52, 53].

The role of endosymbionts in arthropods has been partially described and a strong correlation with pathogen replication and transmission has been shown in some cases. For instance, infection of Wolbachia(+) and Wolbachia(-) Culex quinquefasciatus colonies with WNV revealed a greater proportion of Wolbachia(-) infected mosquitoes developing loftier virus titers in saliva, which is necessary for virus dissemination and manual [54]. This ascertainment led to the suggestion that the difference in susceptibility to WNV infection between Cx. quinquefasciatus and Culex tarsalis might be partially explained by the difference in Wolbachia infection between these two species, since Cx. tarsalis is not infected with Wolbachia [54].

Past applying the metabarcoding approach, we were able to notice several pathogenic species and to confirm several of them past species-specific or genus-specific PCRs. As for Rickettsia and Borrelia genera, the prevalence in our information set is shared by similar studies in Italy and Europe [55–59]. In addition, our findings show that Rickettsia seems to be widespread amid residential and migratory birds, while Borrelia was detected only in short- and mid-altitude migratory birds, suggesting unlike patterns in its transmission.

The ascertainment of bacterial genera in the metabarcoding results not confirmed by the species-specific or genus-specific PCR tests may be explained by the presence of Rickettsia-, Coxiella-, and Francisella-like symbionts. The primer pairs used for the diagnostic tests were retrieved from published studies on the detection of pathogenic species of these genera. Nearly likely, these tests neglect to detect a symbiont species of the targeted genus. As reported for Coxiella, the genetic diversity of symbiont organisms is very high, and little is known about their spread in arthropods, which may explicate the discordance between the results of 16S rRNA gene metabarcoding and diagnostic PCRs [60]. Alternatively, it has been shown that some molecular tests that are specific for C. burnetii also detect Coxiella-like leaner, leading to overestimation of the pathogen species. Indeed, the molecular characterization of bacterial endosymbionts plays a pivotal role in the design of targeted molecular tests for the sole detection of pathogenic species.

Recent studies have shown that C. burnetii could accept originated from a tick-associated antecedent, while the Francisella-like endosymbiont of the hard tick Ambylomma probably evolved from a pathogenic strain of Francisella, indicating that tick endosymbionts can evolve from mammalian pathogens [14,15]. Little is known near these recently uncovered symbionts, perhaps because the research was biased towards the pathogenic species. Such is the example of the Coxiella genus, which only has two species (i.east., burnetii and cheraxi). The majority of studies have described C. burnetii because about isolates were collected from humans or domestic ruminants during Q fever outbreaks. More information on novel Coxiella-like organisms in not-vertebrate species like ticks has been acquired via 16S rRNA gene metabarcoding [fourteen].

Finally, nosotros observed a critical indicate in the bioinformatics analysis of our data. The first point is the erroneous identification of East. ovina by the MSR, not confirmed by deeper analysis. This issue may business concern the used database, since, as reported in the Illumina transmission, the Metagenomics workflow uses an Illumina-curated version of the Greengenes database. The choice of database may also atomic number 82 to different results in taxa assignment. In our analyses, the SILVA database immune united states of america to assign RSVs to Wolbachia, C. Midichloria, and Arsenophonus. Since these three genera represent the majority of the microbial customs, being symbionts, correct taxonomic assignment is very relevant for these kind of studies. We suggest the use of the SILVA database for future projects investigating arthropod microbiota by 16S rRNA metabarcoding.

Our metabarcoding analysis showed that the microbiota living with (and within) arthropods is circuitous, closely related to the host species, and that its major component comprises endosymbiont-related species. This arroyo provides a global overview of the leaner present in/on ectoparasites collected alive from migratory birds. Considering it employs a universal primer set for prokaryotic metabarcoding, this approach was also useful for identifying in one shot the genera that include pathogen species. Since the method does not oftentimes discriminate across the genus level, a second-level, genus- or species-specific investigation was required to ostend the presence of the pathogen species in some samples. Without an overview provided by the metabarcoding method, multiple tests for each pathogen in all the samples would have been needed.

Supporting information

S1 Fig. Map of sampling sites.

Sites in Liguria, Latium, and Sicily were located on the islands of Palmaria, Ventotene, and Ustica, respectively. Each of these map tile sets are Stamen Pattern, nether a Creative Eatables Attribution (CC By 3.0) license.

https://doi.org/10.1371/journal.pone.0202270.s001

(PDF)

S4 Fig. Bar plot representing the relative abundance of the RSVs by genus in the Hippoboscidae diptera.

Abundance is relative to the full microbiota. To better colour-coding readability, RSV numbering is assigned by genus, and so that RSV i in Wolbachia is not the aforementioned as RSV 1 in Arsenophonus.

https://doi.org/10.1371/journal.pone.0202270.s004

(PDF)

S5 Fig. Bar plot representing the relative abundance of the RSVs in ticks for the most common genera.

Abundance is relative to only the genera considered. To improve color-coding readability, RSV numbering is assigned by genus, so that RSV 1 in Wolbachia is non the same every bit RSV 1 in Rickettsia.

https://doi.org/10.1371/periodical.pone.0202270.s005

(PNG)

Acknowledgments

The authors wish to thank Carla Lo Vecchio for laboratory assistance with the PCR tests, Giovanni Savini (Istituto Zooprofilattico Sperimentale dell'Abruzzo east del Molise Giuseppe Caporale, Teramo), Riccardo Orusa (Istituto Zooprofilattico Sperimentale del Piemonte, Liguria e Valle d'Aosta, Aosta), Piergiovanni Piatti (Camera di Commercio, Torino), and Santo Caracappa (Istituto Zooprofilattico Sperimentale della Sicilia, Palermo) for their support in the written report.

The authors are grateful to the two anonymous reviewers for their helpful suggestions in improving the manuscript.

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