Sara Fratini1,*, Stefania Zanet2, Chiara Natali1, Alessio Iannucci1 Dario Capizzi3, Paolo Sposimo4, Claudio Ciofi1
1 Department of Biology, University of Florence, Via Madonna del Piano 6, 50019 Sesto Fiorentino (FI), Italy
2 Department of Veterinary Sciences, University of Turin, largo Braccini 2, 10095 Grugliasco (TO), Italy
4 Nature and Environment Management Operators Srl (NEMO), Piazza Massimo D’Azeglio 11, 50121 Florence, Italy
* Corresponding authors: S. Fratini, E-mail: sara.fratini@unifi.it, Tel: +39 055 4574715. Running title: 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15
Abstract
Keywords Genetic diversity; bottleneck; eradication campaign; Rattus rattus; biological invasions; microsatellites, zoonoses
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Introduction
Rats are regarded as one of the most dangerous pest species in the word due to several reasons. Rats are causal factors in large numbers of extinctions and key threats to many threatened species (Doherty et al., 2016), have a negative impact on agriculture and vegetal structure (Stenseth et al., 2003). Accidental or intentional movements of rats mainly through sea routes have always been very common with a peak starting from the Age of Exploration. To date, the ship rat Rattus rattus is included among the worst invasive species in the world (Lowe et al., 2000). Despite, strict regulation against rat transport (such as ship inspections, and biosecurity measures for docking ships) are generally lacking in many countries.
Rats are also a danger to public health and animal health (Webster and Ellis, 1995; Davis et al., 2005). To date, more than 24 pathogens are directly or indirectly transmitted to man by rodents (Meerburg et al., 2009). Among these, Vector-borne diseases (VBD) such as Leishmaniasis, Anaplasmosis, Babesiosis and Lyme borreliosis, are particularly relevant as their incidence has been rising in Europe in the last decades and their areas of presence have expanded to areas previously free of disease due to anthropic and climatic factors (Daszak, 2000). The majority of VBD present in Europe and in Italy use rodents as intermediate or reservoir hosts. Toxoplasma gondii is the most prevalent zoonotic pathogen worldwide (www.who.int, accessed January 2019) infecting 30-50% of the human population. T. gondii can infect most genera of warm-blooded animals including rodents (Dubey, 1998). The most common source of human infection is represented by ingestion of contaminated food and water. The impact of VBD and T. gondii on public health is accentuated in insular habitats where epidemiologic conditions and population dynamics exasperate the biological cycles of pathogens and of their vectors (Zanet et al., 2014a).
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During the last decades, many rat eradication campaigns have been conducted, particularly in insular systems and forests, to protect biodiversity threatened by their presence and to limit diffusion of zoonosess, and a few years after eradication re-establishment of lost biodiversity has generally been observed (Towns et al., 2001; Graham & Veitch, 2002; Kerbiriou et al., 2004; Pascal et al., 2005). However, there are examples of eradication campaigns that were not as successful, since a complete and stable eradication was not achieved (see Savidge et al., 2012). Several factors may have been responsible for the eradication failure. A reason can be the high capability of rats to re-invade the same environments from interconnected area once they return available to new invaders. For this reason, the ‘‘eradication unit’’ concept (sensu Robertson & Gemmell, 2004), defined as ‘‘the interconnected populations that must be eradicated at the same time to prevent rapid recolonization’’, has been adopted in several eradication plans. Another possible cause of unsuccess of eradication campaigns is the presence of some individuals that survived eradication. (Abdelkrim et al., 2007). The rate of reproduction and growth of rats is so high that even from a few individuals, an area can be reconquered by a viable population relatively quickly (Abdelkrim et al., 2007). In islands, this phenomenon can also be assisted by the absence of a real predator of the rat.
Since the 1950s, rodent pest control has been conducted using first-generation anticoagulant rodenticides, such as warfarin, difacinone and chlorofacinone. These compounds are very powerful since they inhibit blood clotting by blocking Vitamin K reductase reaction and can kill rodents relatively quickly. However, their massive use has been responsible of the onset of the resistance to anticoagulants, observed for the first time in 1958 in England (Boyle, 1960). Rodent resistance to such compounds is another of the main causes of failure of eradication campaigns worldwide. Moreover,
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the occurrence of anticoagulant resistance causes direct and indirect environmental damages: anticoagulants generate very toxic secondary compounds and can enhance the spread of zoonotic diseases (such as hantaviruses, echinococcosis or leptospirosis) because resistant strains are difficult to eradicate.
To date, more than 24 pathogens are directly or indirectly transmitted to man by rodents (Meerburg et al., 2009). Among these, Vector-borne diseases (VBD) such as Leishmaniasis, Anaplasmosis, Babesiosis and Lyme borreliosis, are particularly relevant as their incidence has been rising in Europe in the last decades and their areas of presence have expanded to areas previously free of disease due to anthropic and climatic factors (Daszak, 2000). The majority of VBD present in Europe and in Italy use rodents as intermediate or reservoir hosts. Toxoplasma gondii is the most prevalent zoonotic pathogen worldwide (www.who.int, accessed January 2019) infecting 30-50% of the human population. T. gondii can infect most genera of warm-blooded animals including rodents (Dubey, 1998). The most common source of human infection is represented by ingestion of contaminated food and water. The impact of VBD and T. gondii on public health is accentuated in insular habitats where epidemiologic conditions and population dynamics exasperate the biological cycles of pathogens and of their vectors (Zanet et al., 2014a).
One of the reasons of the genetic bases of anticoagulant resistance in rats (and in general in rodents) is the presence of point mutations in the three exons of the Vitamin K Epoxide Reductase Complex Subunit 1 (VKORC1) protein gene, that result in a few VKORC1 amino acid changes (Rost et al., 2004). Pelz and coauthors (2005) first described eight mutations in the VKRCO1 gene of brown rats, of which five interesting aminoacidic positions 128 and 139. Successively, Grandemange et al. (2009) demonstrated that these mutations by themselves confer resistance to first-generation
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anticoagulants. Up to date, about 30 mutations in VKROC1 have been described in Rattus spp. from many countries around the world (Pelz, 2005; Rost et al., 2009; Tanaka et al., 2012; Goulois et al., 2016; Iacucci et al., 2018). Not all the detected mutations are necessarily associated with resistance, but, as a matter of fact, any frequent no-silent mutation must be considered as a potential cause of resistance due to the high adaptive value of being not sensitive to anticoagulants.
The spread of invasive rodent species (being responsible for predation on a large range of vertebrate and invertebrate species as well as of plant species) have strongly affected the entire Mediterranean area, particularly its islands commonly regarded as hotspots of endemic fauna and flora. For this, there are numerous examples of programs aimed to eradicate invasive rodent species from Western Mediterranean islands (i.e. Molara, Tavolara, Linosa, Pianosa, Montecristo) thus to restore insular ecosystems. (reviewed in Capizzi et al., 2016). The present study takes its place in this context, since it is part of a comprehensive conservation program of endemic plant and animal species by pest control enforced in the Pontine islands (Central Italy) (Celesti-Grapow et al., 2017; http://www.ponderat.eu/en-home). Its main aim is to provide background information to set up an eradication plan of black rats and to draw biosecurity measures to prevent further reinvasion. We assessed patterns of genetic diversity and population structure of black rats from Latium mainland and Pontine Archipelago, genotyping 10 polymorphic autosomal microsatellites, in a total of 119 individuals collected from four localities. These analyses had the scope to define the eradication unit/s of black rats occurring in the Pontine Archipelago, and to depict the demographic history of black rats invaded the Archipelago. We then investigated sequence polymorphisms at the three exons of the VKRCO1 gene to check for the possible occurrence of sequence variants conferring resistance to anticoagulants. Such an investigation has never been
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performed in Italy on black rats, despite resistant phenotypes of rats and mice have been commonly reported in Europe and recently specifically in Italy (Iacucci et al., 2018; Iannucci et al., 2018). Finally, we evaluated the presence and prevalence of pathogens, with particular reference to those transmissible to humans, analyzing a subsample of 38 black rats from the Pontine Archipelago.
Materials and methods
Study area, sample collection and DNA extraction
The Pontine Archipelago is a group of five volcanic islands (Ponza, the main islands from which the island chain takes its name, Palmarola, Ventotene, Santo Stefano and Zannone), placed in the Tyrrhenian Sea and lies off the Gulf of Gaeta (Central Italy) (Fig. 1). The Archipelago is a popular touristic destination in summer, while during the winter some islands are uninhabited. Only Zannone island is part of the Natural Park of Circeo (since 1979), while the other islands are not under protection regulations.
We captured a total of 119 male and female adult samples of Rattus rattus using traps from three islands of the Pontine Archipelago (Palmarola, n = 36; Ventotene, n =49; and Ponza, n = 10) and from a locality on the mainland coast, Monte Orlando (n = 24). Monte Orlando is very close to Gaeta harbour, from which boats sail to Ponza and Ventotene throughout the year. On Ponza island, rats were collected from the harbour where private and tourist boats depart daily to reach the other Pontine Islands.
For each captured rat, 10-50 g of tail muscle tissue was collected and preserved in absolute ethanol. DNA was extracted by overnight digestion of tissues at 55 °C in a lysis buffer containing 0.1 M Tris buffer, 0.005 M EDTA, 0.2 M NaCl and 0.4% SDS,
pH 8.0, and 0.1 mg proteinase K, followed by isopropanol-ethanol precipitation
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(Sambrook and Russell, 2001). Samples were resuspended in DNAase-free water and preserved at -80° C.
VKROC1 sequencing
The totality of the gene encoding for the VKROC1 gene was amplified in all the collected rats using three primer pairs, each pair annealing to intronic regions and specific for one of the three exons. The sequences of the three primer pairs were: exon 1, VKROC1_ex1_F: TCTTCCCTCCTGTSYCTGGG-3’and VKROC1_ex1_R: AAATYATCTGGYAACCTGGC-3’; exon 2, VKROC1_ex2_F:
5’-GGTGGMGCTTCTTGCTAATC-3’ and VKROC1_ex2_R:
5’-GCTCAGTAATTAGCAGCTGGC-3’; and exon 3, VKORC1_ex3_F: 5’–
TTTCACCAGAAGCACCTGCTGYC-3’ and VKORC1_ex3_R: 5’–
ACACTTGGGCAAGGSTCATGTG–3’. Set 1 and 2 were specifically designed by authors for this study, while Set 3 was modified by Grandemange et al. (2009).
The amplifications were performed in a Perkin Elmer 9600 thermal cycler, using 1X Buffer per Taq polymerase, 300 μM dNTPs, 1.5 mM MgCl2, 0,5 μM of each primer, 0.5 U Taq polymerase, and using the following PCR conditions: 35 cycles of denaturation for 45 sec at 94°C, annealing for 45 sec at 52-54°C, extension for 90 sec at 72°C, preceded by an initial denaturation for 5 min at 94°C followed by a final extension for 10 min at 72°C.
Amplicons were then visualized on an 1% agarose gel, purified by precipitation with Sure Clean (Bioline), resuspended in water, and then sequenced with the ABI BigDye terminator mix. Ethanol precipitation was performed after the amplification reaction followed by electrophoresis in n automated DNA sequencer (ABI Prism 310 Genetic Analyzer). 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170
Microsatellite analysis
The totality of black rat samples was screened for polymorphisms at ten microsatellite loci described for R. norvegicus by Jacob et al. (1995) and for R. fuscipes greyii by Hinten et al. (2007) and successfully tested in R. rattus by Savidge et al. (2012), Ragionieri et al. (2013), Willows-Munro et al. (2016) and Iannucci et al. (2018). Each locus was separately amplified by polymerase chain reaction (PCR) using the following PCR condition: 1 µl of DNA, 2 µl of Buffer 10X (Invitrogen), 2 mM of MgCl2, 0.4 ml of each 10 µM primer, 200 µM of each dNTP and 0.4 U of Taq (Invitrogen) in 15 µl of final volume, with 35 cycles of 30 s for denaturation at 94°C, 45 s for annealing at 54-57°C and 180 s extension at 72°C, preceded by 5 min of initial denaturation at 94°C and followed by a 30 min final extension at 72°C.
PCR products were then pooled into three multilocus sets: R1 including D10Rat20, D5Rat83, D7Rat13 and D19Mit2, R2 including D11Mgh5, D16Rat81 and D9Rat13; and R3 including RfgL3, RfgG3 and RfgD6.
Amplicons were resolved by capillary electrophoresis in an Applied Biosystems 3130xl Genetic Analyzer and allele sizes scored against a GeneScan500 LIZ size standard using GeneMapper 5.0 (Applied Biosystems).
Epidemiological investigations
Total genomic DNA was extracted from spleen (≈10 mg), skeletal muscle (≈25 mg of quadriceps femoris), kidney (≈25 mg) and central nervous system (CNS) (≈25 mg of brain homogenate) of 38 rats (Palmarola, n = 13 Ventotene, n =18; and Ponza, n = 7) using GenElute Mammalian Genomic MiniPrepKit (Sigma Aldrich, MO, USA) following manufacturer’s instructions. A 145 base pairs (bp) long specific fragment of L. infantum kDNA was amplified from spleen samples using mRV1–mRV2 primer pair with amplification conditions as reported in Zanet et al. (2014a). Spleen was also tested
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to detect tick-borne pathogens. Specifically, a 400 bp-long fragment of the V4 hypervariable region of the 18S rDNA of protozoa of the genera Babesia and Theileria was amplified according to Zanet et al. (2014b). A 452bp-long fragment of the 16s rRNA gene of bacteria of the genera Anaplasma and Ehrlichia was amplified using primers PER1 and PER2 as reported by Beninati et al. (2006). Borrelia burgdorferi sensu lato was detected by PCR amplification of a 452 bp fragment of the 5S-23S intergenic spacer region using 23SN1-23SC1 primer pair (Rijpkema et al., 1995). Skeletal muscle, kidney and CNS were tested in parallel to detect the presence of T. gondii using a Loop-Mediated Isothermal Amplification (LAMP) as reported in Trisciuoglio et al. (2015). Positive and negative control samples were included in each PCR/LAMP assay and standard precautions were taken to avoid contamination. PCR positive samples were purified and sequenced on both DNA strands (Macrogen, Spain). Obtained sequences were compared to the ones available in GenBank to determine species identification using the software MEGA version 6 (Tamura et al., 2013).
Statistical analysis
Polymorphism sequence variation
The VKROC1 sequences were corrected and aligned using the software Geneious vers. 8.0.5 (Kearse et al., 2012). Single nucleotide polymorphisms (SNPs) were identified by comparison with annotated reference sequences downloaded from GenBank.
Microsatellite data
The data set was checked for scoring errors due to stuttering, allele dropout and evi-dence of null alleles by means of equation 2 from Brookfield (1996), as implemented in Microchecker ver. 2.2.3 (van Oosterhout et al. 2004). Since all populations showed het-erozygote deficiencies at loci D10Rat20 and RfgG3 (imputable to the occurrence of null alleles) we used the software FreeNA (www.montpellier.inra.fr/URLB) to compute a
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genotype dataset corrected for null alleles, following the INA method described in Cha-puis & Estoup (2007). This dataset was then used for calculating the measures of popu-lation variability and in all further analyses (except the Bayesian clustering method). The number of alleles and allelic richness for each locus and population were calculated using FSTAT 2.9.3.2 (Goudet, 1995). Linkage equilibrium among loci and Hardy-Weinberg equilibrium (HWE) were assessed for each population using GENEPOP 4.2.1 (Rousset, 2008). Significance levels were adjusted for multiple tests by using a sequen-tial Bonferroni correction (Rice, 1989). Statistical significance of the estimator f of the inbreeding coefficient FIS was evaluated after 10,000 allele permutations performed in Genetix 4.05 (Belkhir et al., 1996-2004).
To investigate whether individuals from a sampling site can be more related than indi-viduals from different sampling sites if gene flow is negligible, we compared the mean pairwise relatedness calculated for each sampling site to average relatedness estimated across sampling sites using the Lynch and Ritland (1999) estimator. This analysis was run using GenAlex 6.5 (Peakall and Smouse, 2012), obtaining statistical significance af-ter 1,000 permutations of relatedness values.
Genetic divergence among sampling sites was estimated by the exact test for population differentiation implemented in GENEPOP 4.2.1. This test verifies the existence of differences in allele frequencies at each locus and for each population. Single locus significance P-values were calculated using a Markov chain with 1000 batches and 1000 iterations per batch combined over loci using the Fisher method. Genetic differentiation was also assessed by the FST estimator θ using ARLEQUIN 3.5 (Excoffier and Lischer, 2010). Statistical significance of θ values under the null hypothesis of no differentiation among sampling sites was assessed after 10,000 allele permutations. 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245
We estimated recent migration rates using a MCMC as implemented in the software BayesAss vers. 1.3 (Wilson & Rannala 2003). This Bayesian approach, which relies on Markov chain Monte Carlo (MCMC) techniques, estimates the proportion of genotypes in a population composed of migrants over the last few generations. The run consisted of 3 × 106 iterations with a sampling frequency of 2000, and the first 1 × 106 steps were
discarded. Default setting delta values were used.
We also performed a Principal Coordinates Analysis (PCoA) based on genetic distances between individuals assessed by multivariate analysis of loci and samples to investigate the presence of distinct groups. The analysis was conducted using the covariance-standardized method implemented in GenAlex 6.5.
We applied the Bayesian clustering method implemented in STRUCTURE 2.3.4 (Pritchard et al., 2000) to infer the most likely number of genetically distinct clusters (populations) given the observed genotypes and to evaluate the proportion of each individual’s genotype belonging to each inferred population. We used the admixture model as the most appropriate for populations that may have recent ancestors from more than one population (Pritchard et al., 2000). We run 1,000,000 Markov Chain Monte Carlo iterations without prior population information for a number of populations K ranging from 1 to 4 using a burn-in period of 20,000 iterations. We calculated the mean likelihood over three runs for each K with correlated allele frequencies and estimated the most likely number of clusters as described in Evanno et al. (2005). The K value with the highest ΔK was then used as prior information to estimate the proportion of membership of each genotype in each of the K populations. Results were graphically visualized using STRUCTURE PLOT (Ramasamy et al., 2014)
Evidence of bottlenecks was assessed for the four R. rattus sampling sites using BOTTLENECK 1.2.02 (Cornuet and Luikart, 1996). Populations that have experienced
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a recent reduction in their effective population size are expected to exhibit a corresponding reduction in the number of alleles and gene diversity. In particular, the number of alleles decreases faster than gene diversity so that, in a recently bottlenecked population, the observed gene diversity is higher than the average gene diversity expected from the observed number of alleles in a population of constant size at mutation-drift equilibrium (Luikart et al., 1998). The average gene diversity expected at equilibrium was calculated from a distribution of 10,000 simulated gene diversities under the two-phase mutation model (TPM) and the step-wise mutation model (SMM) of microsatellite evolution. For the TPM, we set 70 multi-step mutations with a 12% variance among multi-steps (Piry et al., 1999), and obtained statistical significance based on 1,000 replications. Gene diversity excess was assessed using a Wilcoxon sign-rank test (Luikart et al., 1998). We also assessed whether the observed allele frequencies at each locus deviated from an L-shaped distribution expected under mutation-drift equilibrium (Luikart et al., 1998 ).
We also calculated the Garza-Williamson (2001) index (M) to test for a reduction in rat population size using ARLEQUIN 3.5. The M index is a ratio of the number of alleles observed in a sample divided by the number of alleles expected under the observed allele size range. Garza and Williamson (2001) reported that M values greater than 0.82 should be representative of stable populations that have not suffered a known reduction in size, whereas values of the M index lower than 0.68 indicate a bottleneck or a founder event.
To identify variables associated with infection of each pathogen, generalized linear models were implemented in the statistical environment R 3.5.1 (R Core Team, 2018) with PCR result as dichotomous response variable.
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Results
VKRCO1 sequence variation
We amplified three fragments of the VKRCO1 gene, respectively 253 bp, 272 bp and 308 bp long (excluding the primers), whose combination allowed us to analyze the entire coding region of the gene, including. 160 aminoacids. A total of 4 SNPs was found in black rat sequences, of which one in exon 1, one in exon 2 and 2 in exon 3 (Table 1). All are silent mutations, i.e. not responsible of aminoacidic changes.
Microsatellite data
No significant linkage disequilibrium was recorded across populations and across loci. All loci were polymorphic, with number of alleles ranging from 4 (locus RfgD6) to 20 (locus D7Rat13). Relatively high levels of molecular variation were recorded at all sampling sites (Table 2). Allelic diversity and average allelic richness were similar for all sampling sites, ranging from 6.50 ± 0.75 to 7.30 ± 0.94 and from 5.04 ± 0.55 to 6.29 ± 0.69, respectively (Table 2). The total number of private alleles ranged from 7 to 19 with the highest number assessed in the mainland sampling site Monte Orlando (Table 2). The lowest values of expected and observed heterozygosity were recorded for Palmarola (Table 2). No sampling site deviated from HWE after Bonferroni correction, except Palmarola at locus RfgD6 (Table 2). Fis index estimator f was negative and significant for Palmarola and Ventotene islands (Table 2).
Average pairwise relatedness based on the Lynch and Ritland (1999) estimator for the four sampling sites were: Monte Orlando, r = 0.083; Palmarola, r = 0.102; Ventotene, r = 0.079; and Ponza, r = 0.073. All values were higher than the average relatedness calculated among all individuals across locations (r = -0.004 ± 0.001, P < 0.001).
There was a strong genetic differentiation among sampling sites. The Fisher exact test rejected the hypothesis of genetic homogeneity of allele frequency distributions (X2 = ∞, 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 313 314 315 316 317 318 319 320
df = 20, P < 0.001). Significant differentiation was also recorded by F-statistics performed across populations (θ = 0.27, P < 0.001) and between all pairwise population comparisons (Table 3). The recent migration rates between pairs of rat localities vary between 0.004 and 0.012, while the proportion of self-recruitment within each locality is always higher than 0.95 (Table 4).
Principal component 1 and 2 explained 18.08% and 8.69% of genetic variation, respectively, and clearly separated the Monte Orlando black rats from those collected in the three Pontine islands (Fig. 3). Component 1 also clearly separated individuals from Palmarola and Ventotene, while individuals from Ponza were partially overlapped to those from the other two Pontine islands (Fig. 3).
Population structure Bayesian analysis revealed that the most probable number of clusters for interpreting the observed genotypes was K = 3 based on the highest modal value of ΔK = 4705.40 estimated using the Evanno et al. (2005) method (Fig. S1, Supporting Information). Three main partitions were used as prior population information for calculating the posterior probability of individual assignment (Fig. 2). Individuals from Monte Orlando were nearly entirely assigned to cluster 3 (98%), those from Palmarola and Ventotene to cluster 1 (98%) and 2 (99%), respectively. The Ponza sampling site was the most admixed, with 75.6% of individuals assigned to cluster 1, 15.3% to cluster 2 and 9.1% to cluster 3.
The heterozygosity excess approach performed under the stepwise and two-phase models of microsatellite mutation reported no evidence of reduction in effective population size (Table 5). The Palmarola black rat population showed evidence of heterozygosity deficiency under the stepwise model of microsatellite. Moreover, all four locations had a clear L-shaped allele frequency distribution. On the other hand, the M ratio index varied from 0.22 to 0.26 suggesting a bottleneck event in all island
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populations. The highest M values were recorded for black rats from Palmarola (Table 5).
Epidemiological investigations
The 38 rats (15 females and 23 males) tested for zoonotic pathogens had an average weight of 162.98 gr (s.d. 46.85 gr). All appeared to be in satisfactory body conditions, and no gross lesions were reported at necropsy.
L. infantum DNA was detected in the spleen of 2 individuals with a prevalence P= 5.26% (CI95% 1.46% - 17.29%). Both positive rats were females trapped in Ventotene island.
Babesia piroplasms were detected in 14 rats, corresponding to 36.84% (CI95% 23.38% - 52.72%) of the tested animals. No significant difference was recorded in infection prevalence among different sex, age classes nor by island of origin of the animals (Table 6). All isolates were sequenced and identifies to species level as Babesia microti. Borrelia afzelii DNA was amplified from an adult female rat from the island of Ventotene. This rat is one of those resulted to be infected with B. microti.
Any specimen was positive to Anaplasma/Ehrlichia spp. PCR. T. gondii DNA was detected with a prevalence of 42.11% (IC95% 27.85% - 57.81%), with 15 rats testing positive on muscle-extracted DNA and 1 individual on kidney-extracted DNA. No significant difference was recorded in infection prevalence among different sex, age classes nor by island of origin of the animals even if a higher prevalence were reported in the rats from Palmarola (P=46.15%, CI95% 23.21% - 70.86%, p>0.05) (Table 6).
Discussion and conclusions VKRCO1 sequence variation
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In the Pontine islands and on the Latium mainland facing them we did not register the presence of black rat individuals with mutations in subunit 1 of the VKRCO gene known to confer resistance to common anticoagulants. Up to date, most of these muta-tions (about 30) have been detected in R. norvegicus (Pelz et al, 2005; Rost et al., 2009), while only six have been specifically reported for R. rattus (Tanaka et al., 2012; Goulois et al., 2016). In Europe, resistance to rodenticides is frequently observed in R. norvegi-cus, but very rarely in R. rattus. Only recently Goulois et al. (2016), trapping black rats on a Spanish farm, detected the first mutation (Y25F) in the VKROC1 gene of R. rattus in Europe and associated it to the resistance to bromadiolone. This new mutation has not been found in our trapped rats.
Since we detected only five synonymous mutations in VKROC1 coding sequence, we can state that up to date the spread of resistance to anticoagulants in R. rattus has not yet affected our area of study. However, we cannot exclude that some mutations should ap-pear in the next generations under the selective pressure exerted by the use of the first-generation anticoagulants as pest control in the Pontine Archipelago. This argument is supported by the fact that Iannucci et al. (2019) reported the presence of a resistant house mouse collected in this archipelago.
In Europe, the diffusion of warfarin resistance is much greater in the domestic mouse than in individuals of the genus Rattus (Goulois et al., 2017). This is attributed to a greater selective pressure exerted by the first-generation rodenticides on the domestic mouse (Goulois et al., 2017). The control of domestic mice, in fact, is essentially carried out by non-professionals, who tend to exceed with the use of rodenticides not being aware of the consequences that a massive use of these molecules can have on the spread of resistance. On the contrary, rat control is usually performed by informed profession-als, aware of the risks associated with the use of these molecules (Goulois et al., 2017).
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Definition of the Pontine Archipelago eradication unit
This study recorded a strong population structure and absent or very limited gene flow among the three analysed islands of the Pontine Archipelago (Ponza, Palmarola and Ventotene) and the mainland locality of Monte Orlando, on the Latium coast facing the Archipelago. Based on differences in allele frequency distribution, analysis of variance, PCoA and Bayesian clustering approaches, we concluded that the black rats of Palmarola and Ventotene belong to two distinct populations and would be designed as separate eradication units.
On the contrary, the black rats of Ponza genetically overlap, at least partially, to both the black rats from Palmarola and Ventotene. This leads us to conclude that this island does not belong to a distinct eradication unit, but to both Ventotene and Palmarola eradication units. Ponza is the main island of the Pontine Archipelago from which ferries and private boats daily sail towards the other Pontine islands and towards the ports located on the Latium coast (i.e. Gaeta, Formia, Terracina and Anzio). Therefore, this suggests that one of the possible black rat source populations of Palmarola and Ventotene may be the port of Ponza, and that at least part of the black rats on Palmarola and Ventotene arrived on these islands transported by boats set sail from Ponza. However, we cannot rule out the presence of other source populations not included in this study and that the movement of black rats could follow an inverse flow, that is towards Ponza from Ventotene and Palmarola. Anyway, since the rates of migration between pairs of locations are close to zero and the self-recruitment rates within each location are close to the maximum value of 1, it seems plausible that in recent times (i.e. over the last generations) there has not been any significant exchange of individuals between these Pontine islands.
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As regards the black rats from Monte Orlando (very close to the port of Gaeta from which boats sail to Ponza and Ventotene throughout the year), they are totally genetically separated from those sampled in the Pontine islands. This clearly indicates that this group of black rats is not a source population of the Pontine islands and belongs to a distinct eradication unit.
The indices of genetic variability (number of alleles, allelic richness and number of private alleles) and the observed heterozygosity values estimated for the four black rat populations are in line with what is reported for other island systems (eg Abdelkrim et al., 2009; Savidge et al., 2012; Ragionieri et al., 2013; Iannucci et al., 2018). Two insular populations (Palmarola and Ventotene) have a significant excess of homozygotes: this is common in island populations, usually small and isolated, and may be due to the presence of family groups and inbreeding phenomena (Frankham et al., 2010). This is also suggested by the high values of non-migrant individuals registered in these locations. This may be also due to a founder effect, bottleneck event, genetic drift and/or limited gene flow (Frankham et al., 2010).
Population demographic history
We depicted the demographic history of our populations applying three different methods (heterozygosity excess, shifts in allele frequencies and low ratios of allelic number to allelic size range) and we obtained apparently incongruent results as already reported in Iannucci et al. (2018) for the Tuscan Archipelago. Only the M-ratio tests, in fact, showed clear evidence of bottleneck events for all our populations, while the heterozygosity excess approach not revealed any evidence of reduction in effective population size. As discussed in Iannucci et al. (2018) and following Marshall et al. (2009) and Garza and Williamson (2001), the M-ratio test recovered evidence of reduction in population size farther in the past respect to the other two methods, being
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sensitive to historical bottlenecks. The very low M-ratio values recorded in this study therefore suggests that all our populations passed through a drastic reduction in population size in the past, bringing yet the signature of an old founder effect (Abdelkrim et al., 2005a; Iannucci et al., 2018).
The presence of R. rattus in Central Italy is dated back 1500 years before present (De Grossi Mazorin, 1987; Colangelo et al., 2015) and its origin within the entire Western Mediterranean basin has been unexpectedly attributed to a single colonization event (Colangelo et al., 2015). Despite the long and complex history of colonization and trade of the Mediterranean basin and the concrete opportunity for multiple introductions over millennia, Colangelo et al. (2015) recorded a low genetic diversity at mitochondrial loci in Western Mediterranean black rats and populations clearly out of equilibrium.
In their study, Colangelo et al. (2015) analysed black rats collected from Ponza and reported for this locality a high haplotype and nucleotide diversities and the presence of private haplotypes respect to some populations from the Latium coast. This was interpreted as due to a recent genetic diversification in situ after colonization (Colangelo et al., 2015). Our results seem to confirm this hypothesis, since we recorded, on one side, a null current gene flow between Ponza and Monte Orlando and, on the other side, a light admixture of Ponza black rats with those from Monte Orlando.
Epidemiological investigations
After their establishment, several reasons can explain isolation of black rat invasive populations and bottleneck events. First, phenomena of intra-specific competitions of rats against new invaders bring to the creation of familiar groups of conspecifics (Granjon & Ceylan, 1989). The massive use of rodenticides devoted to pest control and
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the spread of zoonotic diseases, carried by parasites as flies and ticks, can be another cause of drastic reduction in population size.
The epidemiological assessment on black rats has evidenced the presence of T. gondii and of vector-borne pathogens, specifically L. infantum, Babesia microti and B. afzelii. B. microti is the species of Babesia responsible of the most widespread zoonotic infections in North America (Spielman, 1994). In Europe, recent studies have shown a prevalence of B. microti in humans much higher than previously hypothesized (Foppa et al., 2002). The differences in prevalence found among the three islands (although not statistically significant) evidenced a greater risk of infection for the rats of Palmarola and Ventotene compared to those of Ponza. Considered the biology of the vector I.
ricinus, the less urbanized environment of Ventotene and Palmarola probably favors the
persistence of the vector (Medlock et al., 2013). The potential zoonotic role of B. microti should be further investigated together with the epidemiological role of vector ticks in terms of species present, abundance and seasonal patterns.
Ixodes ricinus is among the most common ticks in Italy (Maurelli et al., 2018). Its competence as a vector for B. microti has been experimentally confirmed (Foppa et al., 2002). I. ricinus is also the main vector for B. burgdorferi s.l., the etiologic agent of Lyme Borreliosis. Co-infection of ticks with B. microti and B. burgdorferi s.l. is widely reported (Mehr-Scherrer, 1999). In the present study, the only positive rat for B. afzelii was also infected with B. microti. The low prevalence of B. burgdorferi s.l. is in accordance to previous data from Southern Italy (Ciceroni et al., 2001).
L. infantum was detected with a lower prevalence compared to that reported in similar studies from southern Italy, where the parasite is hyperendemic (Cringoli et al., 2002; Rossi et al., 2008), and from Montecristo island (Zanet et al., 2014a). To our
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knowledge, no data are available on infection prevalence in the autochthonous dog population within the study area, nor on phlebotomine sandflies.
The high prevalence of T. gondii infection demonstrates a wide circulation of the parasite in the studied populations. Further studies are needed to depict the relative importance of parasite transmission by ingestion of oocysts compared to infection by consumption of tissue bradyzoites from intermediate hosts like rats. Furthermore, genotyping of the circulating strains could give useful indications to better understand the geographic origin of the parasites and the possible role, as intermediate hosts, of seabirds and migratory birds (Prestrud et al., 2007).
Acknowledgements
We are grateful to Flavia Fineschi, Alberto Masoni and Caterina Zuccagnoli for assistance with genetic analysis. We also thank XX for providing us black rat specimens. This research was funded by the European Commission LIFE project "Restoring the Pontine Archipelago ecosystem through the management of rats and other invasive alien species - PonDerat LIFE14 NAT/IT/000544".
The authors declare no conflicts of interest. Informed consent was obtained from all individual participants included in the study.
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Figure legends
Figure 1. Map of the study sites. Black rat samples for genetic analyses were collected in Monte Orlando (MO), Palmarola (PA), Ventotene (VE) and Ponza (PO); while those for epidemiological investigations in PA, VE and PO.
Figure 2. Plot of proportions of black rats’ genome belonging to each of the three clus-ters considered most likely to account for the observed R. rattus genotypes. Each indi-vidual is represented by a vertical line partitioned into K = 3 segments (dark grey, light grey, black) with lengths corresponding to the proportion of its genome originating from each of the three clusters inferred by a model-based Bayesian method. Black vertical bars define distinct island sampling sites. Location acronyms as in Fig. 1
.
Figure 3. Principal component analysis (PCoA) plot based on ten microsatellite loci showing patterns of genetic divergence among black rats sampled on the Islands of Palmarola, Ventotene and Ponza, and on the mainland locality of Monte Orlando. Principal component (PC) 1 and PC 2 explain 18.08% and 8.69% of genetic variation, respectively. 732 733 734 735 736 737 738 739 740 741 742 743 744 745 746 747 748 749 750 751 752
Table 1 VKORC1 mutations found in Rattus rattus from Pontine Archipelago and Latium mainland.
Mutations Exon WT codon Mut codon WT AA Mut AA
Rattus rattus
A41A 1 GCG GCA Ala Ala
L97L 2 TTA CTA Leu Leu
S110S 3 TCC TCT Ser Ser
A143A 3 GCG GCA Ala Ala
WT codon, wild-type codon; Mut codon, mutated codon; WT AA, wild-type amino acid; Mut AA, mutated amino acid.
753 754 755 756 757 758 759 760
Table 2 Genetic diversity measures in R. rattus from four sampling sites in the Pontine Archipelago and Latium mainland.
Sampling site (n) Locus Allele Range NA AR AP HO HE f M O N T E O R L A N D O , G A E T A ( N = 2 4) D19Mit2 193-249 10 6.94 5 0.83 0.79 -0.097 D7Rat13 156-192 6 4.99 4 0.57 0.63 0.087 D5Rat83 171-195 7 5.92 2 0.78 0.73 -0.051 D10Rat2 0 103-119 7 6.01 0.90 0.72 -0.180 D16Rat8 1 147-169 6 5.10 0.67 0.66 0.026 D9Rat13 114-128 5 4.34 1 0.38 0.43 -0.012 D11Mgh 5 240-278 8 5.98 3 0.75 0.75 0.044 RfgL3 247-263 7 5.12 1 0.71 0.60 -0.128 RfgG3 213-239 10 6.96 3 0.63 0.60 0.069 RfgD6 261-279 4 3.59 0.50 0.38 -0.258 All loci / 7.0 ± 0.61 5.5 ± 0.34 19 0.67 ±0.05 0.63 ±0.04 -0.046 P A L M A R O L A ( n = 3 6) D19Mit2 215-231 9 6.48 1 0.57 0.67 0.013 D7Rat13 154-198 11 7.44 4 0.71 0.75 -0.011 D5Rat83 173-199 6 4.54 3 0.36 0.41 0.020 D10Rat2 0 103-111 6 4.61 0.56 0.54 0.007 D16Rat8 1 147-167 3 2.25 0.03 0.03 0.036 D9Rat13 114-132 6 4.05 0.42 0.41 -0.093 D11Mgh 5 240-286 10 6.42 5 0.53 0.58 0.004 RfgL3 223-265 11 6.52 2 0.79 0.67 -0.024* RfgG3 219-235 8 5.38 0.69 0.66 -0.010 RfgD6 265-279 3 2.69 0.67 0.45* -0.508 All loci / 7.3 ± 0.94 5.04 ± 0.55 15 0.53 ±0.07 0.52 ±0.07 -0.044* D19Mit2 217-233 7 5.33 1 0.53 0.64 0.054 D7Rat13 168-186 7 5.58 1 0.80 0.77 -0.022 D5Rat83 175-195 4 3.62 0.61 0.53 -0.109 D10Rat2 107-123 7 5.72 2 0.61 0.68 0.008 761 762 763 764 765 766 767
V E N T O T E N E ( n = 4 9) 0 D16Rat8 1 157-169 5 4.36 1 0.80 0.67 -0.065 D9Rat13 104-132 12 8.05 2 0.76 0.82 0.015 D11Mgh 5 240-278 6 3.47 1 0.61 0.53 -0.145 RfgL3 225-257 7 5.37 2 0.83 0.77 -0.066 RfgG3 219-241 8 6.20 3 0.69 0.71 0.053* RfgD6 261-279 4 3.27 0.29 0.25 -0.159 All loci / 6.7 ± 0.73 5.10 ± 0.46 13 0.65 ±0.05 0.64±0.0 5 -0.036* P O N Z A ( n = 1 0) D19Mit2 179-231 9 8.59 1 1.00 0.81 -0.146 D7Rat13 158-186 10 9.30 1 1.00 0.86 -0.139 D5Rat83 173-195 5 4.99 0.40 0.53 0.100 D10Rat2 0 101-119 6 5.80 1 0.70 0.76 0.007 D16Rat8 1 159-167 4 4.00 1 0.22 0.31 0.304 D9Rat13 110-130 9 8.59 2 0.22 0.88 -0.013 D11Mgh 5 240-276 6 5.78 0.60 0.64 0.061 RfgL3 231-259 8 8.00 0.89 0.84 0.015 RfgG3 207-241 5 4.90 1 0.80 0.76 -0.007 RfgD6 265-279 3 3.00 0.20 0.19 -0.340 All loci / 6.5 ±0.75 6.29 ± 0.69 7 0.66 ±0.09 0.66 ±0.08 -0.029
NA, number of alleles; AR, allelic richness; AP, number of private alleles; HO, observed heterozygosity; HE, expected unbiased heterozygosity; f, FIS index estimator. Means ± SE values. *, P < 0.005 (after Bonferroni correction).
768 769 770 771 772 773
Table 3 Pairwise comparison matrix of the FST estimator θ between black rat sampling sites (below diagonal) and corresponding P values (above diagonal). Significant P values < 0.008 after Bonferroni correction.
Monte Orlando Palmarola Ventotene Ponza Monte Orlando < 0.001 < 0.001 < 0.001 Palmarola 0.34 < 0.001 < 0.001 Ventotene 0.19 0.31 < 0.001 Ponza 0.22 0.22 0.17 774 775 776 777 778 779 780 781
Table 4 Mean (± SE) and 95% confidence intervals (in parentheses) of Bayesian posterior distribution of recent migration rates between pairs of localities. Values along the diagonal axis represent the proportion of non-migrants in each site.
Monte Orlando Palmarola Ventotene Ponza
Monte Orlando 0.987 ± 0.013(0.954 - 1.00) (0.000 - 0.017)0.003 ± 0.004 (0.000 - 0.011)0.002 ± 0.003 (0.000 - 0.057)0.012 ± 0.016 Palmarola (0.000 - 0.023)0.004 ± 0.007 0.991 ± 0.008(0.968 - 1.00) (0.000 - 0.012)0.002 ± 0.004 (0.000 - 0.056)0.011 ± 0.015 Ventotene (0.000 - 0.023)0.004 ± 0.006 (0.000 - 0.015)0.003 ± 0.004 0.993 ± 0.007(0.972 - 1.00) (0.000 - 0.091)0.025 ± 0.025 Ponza (0.000 - 0.021)0.004 ± 0.006 (0.000 - 0.016)0.003 ± 0.004 (0.000 - 0.014)0.002 ± 0.004 (0.864 - 0.996)0.950 ± 0.035 782 783 784 785 786 787 788 789 790 791 792 793 794
Table 5 Results of the heterozygosity excess and M-ratio tests to assess evidence of population bottleneck in black rats from Monte Orlando (Gaeta) and Pontine Islands.
Heterozygosity excess test M-ratio test
TPM SMM
Location Nexc Ratio PTPM Nexc Ratio PSSM Mode M-ratio Monte Orlando 5.96 5:5 0.54 5.92 9:1 0.99 L-shaped 0.22 Palmarola 5.90 5:5 0.65 5.91 8:2 0.99 L-shaped 0.26 Ventotene 5.95 2:8 0.08 5.94 8:2 0.98 L-shaped 0.24
Ponza 5.95 4:6 0.38 6.20 5:5 0.68 L-shaped 0.24
TPM, two-phase model of microsatellites mutation; SMM, stepwise model of microsatellites mutation; Nexc, expected number of loci with heterozygosity excess under mutation-drift equilibrium; Ratio, number of microsatellite loci exhibiting heterozygosity deficiency vs. excess; PTPM and PSSM are proba-bility values for the Wilcoxon test for heterozygote excess under the TPM and SMM models, respec-tively. Mode indicates a L-shaped normal distribution or a shifted distribution.
795 796 797 798 799 800 801 802 803 804 805 806
Table 6 Number of animals testing positive by PCR and total number of sampled animals for each pathogen in relation to potential risk factors.
Toxoplasma gondii Babesia microt Borrelia afzelii Leishmania infantum
N. positive/N. total (P) Island of origin Ponza 3/7 (42.86%) 2/7 (28.57%) 0/7 (0.00%) 0/7 (0.00%) Ventotene 7/18 (38.89%) 7/18 (38.89%) 1/18 (5.56%) 2/18 (11.11%) Palmarola 6/13 (46.15%) 5/13 (38.46%) 0/13 (0.00%) 0/13 (0.00%) Age Juvenile 4/14 (28.57%) 3/14 (21.43%) 0/14 (0.00%) 0/14 (0.00%) Adult 12/24 (50.00%) 11/24 (45.83) 1/24 (4.17%) 2/24 (8.33%) Sex Male 12/23 (52.17%) 7/23 (30.43%) 0/23 (0.00%) 0/23 (0.00%) Female 4/15 (26.67%) 7/15 (46.67%) 1/15 (6.67%) 2/15 (13.33%) P prevalence 807 808 809 810 811
Figure 1 812 813 814 815 816 817 818
Figure 2
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Figure 3
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