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\begin{document}

\title{Combining host genetic structure and serology to investigate
rabies-related lyssaviruses in the greater mouse-eared bat (Myotis
myotis)}



\author[1]{Stefania Leopardi}%
\author[1]{Marzia Mancin}%
\author[1]{Barbara Zecchin}%
\author[1]{Angela Salomoni}%
\author[2]{Bianca Zecchin}%
\author[3]{Pamela Priori}%
\author[3]{Dino Scaravelli}%
\author[1]{Paola De Benedictis}%
\affil[1]{Istituto Zooprofilattico Sperimentale delle Venezie}%
\affil[2]{Istituto Zooprofilattico Sperimentale delle Venezie (IZSVe)}%
\affil[3]{S.T.E.R.N.A. \& Museo Ornitologico "F.Foschi"}%


\vspace{-1em}



  
  \date{June 17, 2024}


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\selectlanguage{english}
\begin{abstract}
European bat lyssavirus 1 (EBLV-1) is widespread and frequent in
European bats, particularly of the genus Eptesicus. However, other
species can be seropositive, suggesting a complex ecology still mostly
unknown. In Italy, EBLV-1 antibodies are described since 2012 in South
Tyrolean Myotis myotis. This study provide phylogenetic evidence for
either the current or the recent movement of M. myotis from continental
Europe to South Tyrol across the Alpine valleys, which might allow for
the introduction of LYSVs. Serological analyses confirmed antibodies
against EBLV-1 in this bat across the entire region, showing marked
seasonal pattern and a sharp peak of positivity in late summer. No
statistical difference was detected between the maternity colonies
investigated in either the likelihood for infection or the antibody
titres. Indeed, South Tyrolean populations of M. myotis showed no
significant genetic differentiation using nuclear and mitochondrial
markers, supporting the existence of a regional meta-population and a
low philopatric behaviour. This structure, never described for M. myotis
elsewhere, well explains the spread and maintenance of LYSVs trough the
movement of female bats between colonies. Since no virus was detected in
the study, we cannot exclude that our serological data don't derive from
a cross-reaction with an unknown LYSV. However, because all LYSVs can
cause clinical rabies in humans, this study has a strong impact on
public health regardless of the viral species actually circulating. In
addition, the unravelling of the peculiar genetic structure of South
Tyrolean M. myotis is crucial to inform conservation strategies for this
endangered species.%
\end{abstract}%



\sloppy


\textbf{Keywords}

Lyssavirus, bats, \emph{Myotis\_myotis} , genetic, population

\textbf{Introduction}

Today, the role of bats as important reservoir of zoonotic viruses is so
widely accepted as highly discussed (Joffrin, Dietrich, Mavingui, \&
Lebarbenchon, 2018; Wang \& Anderson, 2019; Wilkinson \& Hayman, 2017).
Among these pathogens, the association between vampire bats and rabies
has been long known, along with the evidence that several bat species
might harbor and transmit rabies virus (RABV) in the Americas, as well
as rabies-related lyssaviruses (LYSVs) worldwide (Johnson,
Ar\selectlanguage{ngerman}échiga-Ceballos, \& Aguilar-Setien, 2014; Shipley et al., 2019;
Velasco-Villa et al., 2017). Interestingly, while RABV is responsible
for all bat-associated human cases in the Americas, this virus is not
found in chiropters from the rest of the globe, where up to other 14 of
the 16 known LYSVs have been described instead (Shipley et al., 2019;
Walker et al., 2018).

In Europe, six rabies-related lyssaviruses (RRLVs) have been described,
namely \emph{European bat 1 lyssavirus} (EBLV-1), \emph{European bat 2
lyssavirus} (EBLV-2), \emph{Bokeloh bat lyssavirus} (BBLV), \emph{West
Caucasian bat lyssavirus} (WCBV), \emph{Lleida bat lyssavirus} (LLEBV)
and \emph{Kotalahti bat lyssavirus} (KBLV), with the last one still
waiting for official classification from the International Committee on
Taxonomy of Viruses (ICTV) (Walker et al., 2018). Among these, EBLV-1 is
the most frequently reported, is widespread in the continent and, more
recently, in Great Britain (Middlemiss, 2019). Notably, EBLV-1 has been
associated with spillover events to non-flying mammals and human cases
(Dacheux et al., 2009; Müller et al., 2004; Shipley et al., 2019;
Tjørnehøj, Fooks, Agerholm, \& Rønsholt, 2006). Serotine bats have been
long considered the reservoir for EBLV-1, because the majority of cases
are reported in \emph{E. serotinus} and \emph{E. isabellinus.} However,
the discordance between the genetic structure of \emph{E. serotinus} and
EBLV-1 isolates in France suggests that other species might be involved
in the spread of the virus (Troupin et al., 2017). This hypothesis is
further supported by serological studies showing exposure of several
other bat species, including the grater mouse-eared bat (\emph{Myotis
myotis} ) in Spain, France, Germany, Croatia and Italy (Leopardi et al.,
2018; Picard-Meyer et al., 2011; Schatz et al., 2014; Serra-Cobo et al.,
2013; \selectlanguage{polish}Š\selectlanguage{english}imi\selectlanguage{polish}ć \selectlanguage{english}et al., 2018). Although this bat species seems to mostly
move locally between summer and winter roosts, longer transboundary
migrations have also been recorded (Hutterer et al., 2005), which might
contribute to virus dispersal. However, the relationship between the
home range of \emph{M. myotis} and the circulation of EBLV-1 has never
been investigated, also because the pattern of movements is not clearly
defined and the virus is yet to be characterized from this species. In
particular, the lack of viral detection in \emph{M. myotis} prevents any
conclusion about its role in the epidemiology of EBLV-1, as
sero-positivity might also reflect cross-reactivity with yet unknown
related LYSVs (Kuzmin et al., 2008; Wright et al., 2008).
Indeed,\emph{Myotis} bats have frequently been associated with other
LYSVs, including EBLV-2 in \emph{M. daubentonii} and \emph{M. dasycneme}
, BBLV in \emph{M. nattereri} and the newly described KBLV in \emph{M.
brandtii} .

In this study, we investigated the genetic structure of the greater
mouse-eared bat collected from five maternity colonies in South Tyrol,
the northernmost region in Italy bordering the Austrian territories of
North Tyrol, to investigate the connectivity between them and,
indirectly, the effect of the Alps as natural barrier for animal
dispersal. We further tested for potential sex-biased dispersal and
assessed the fidelity of females to their natal roost (defined as female
phylopatry), features that are common in temperate bats (Kerth, Mayer,
\& K\selectlanguage{ngerman}önig, 2000; Kerth, Mayer, \& Petit, 2002; Moussy et al., 2015,
2013). We therefore interpreted serological data obtained from these
colonies, along with genetic information and environmental parameters,
in the attempt to understand infection dynamics of RRLV in
\emph{Myotis}bats within the study area, even in the absence of
molecular characterization (Peel, McKinley, et al., 2013).

\textbf{Materials and methods}

Animal sampling

In 2016 we investigated five maternity colonies of greater mouse-eared
bats located in the roof of five active churches of South Tyrolean
valleys, the northernmost region in Italy. From each colony, a mean
number of 32 individuals were captured within their roost during the
day, manually or using hand nets according to the structure of the roof
and the position of the colony, and placed in individual cotton bags to
rest for 10-15 minutes. All animals were inspected and measured to
determine the species, age, sex and physiological status. Relevant
measurements included the length of the upper tooth row
(CM\textsuperscript{3}), which is critical to resolve morphological
taxonomy of our target species \emph{M. myotis} against the
sibling\emph{M. blythii,} which has sporadically been reported in the
area (Arlettaz, Ruedi, \& Hansser, 1991). From each animal, we collected
a tissue sample from the right patagium using a 3 mm biopsy punch and
20-100 \selectlanguage{greek}µ\selectlanguage{english}l of blood from the uro-patageal vein using a 300 \selectlanguage{greek}µ\selectlanguage{english}l insulin
syringe with a 30 G needle. Biopsies and blood samples were used for
genetic and serological studies, respectively. All procedures were
performed under physical restraint for a maximum of 6
minutes/individual; after sampling, animals were given water to prevent
dehydration and were placed in a ventilated cotton bag for small animal
transport in groups of 15, until release within the roost. All roosts
were sampled twice around mid-May and mid-September, before and after
the birth pulse, respectively. A total of 318 blood samples and 338
uropatageal biopsies were collected for the purpose of the study. All
personnel working with bats was vaccinated against rabies and showed a
protective antibody titer throughout the duration of the project (WHO,
2018).

Genetic structure of M. myotis from South Tyrol

DNA was extracted from wing biopsies using the DNeasy blood and tissue
commercial kit (QIAGEN) according to the manufacturer's instructions.
The partial cytochrome b (cytb) was amplified as described elsewhere
(Irwin, Kocher, \& Wilson, 1991), in order to confirm the identification
based on morphological parameters. Only samples genetically confirmed
as\emph{M. myotis} (n=166) were included in the following analyses.

The genetic structure of the target population was determined combining
analyses based on nuclear DNA (bi-parental inheritance) and
mitochondrial DNA (maternal inheritance), in order to account for
sex-biased gene flow. In addition, we used only data from females
sampled from each of the five colonies during the same week in May
(Table 1), thus avoiding possible issues related to animal movements
during the reproductive season. On the other hand, we considered the
sampling of adult males within maternity colonies as occasional and
excluded these individuals (n=11 sampled in May) from analyses.

Nuclear genetic structure was investigated using microsatellites
available for this species in the literature (Castella, Ruedi, \&
Excoffier, 2001) (Table S1). Forward primers were labelled with
florescent dyes (MWG-Operon) and PCR amplification was carried out in
three multiplex mixtures containing 10-20 ng of template DNA, using the
Qiagen multiplex kit (QIAGEN) (Table S1). The amplification protocol was
as follows: initial denaturation step at 95\selectlanguage{ngerman}°C for 15 minutes; 35 cycles
of denaturation for 30 seconds, annealing at 60°C, 55°C or 50°C for 90
seconds for mix 1, 2 and 3 respectively, and extension at 72°C for 1
minute; final extension step at 72°C for 10 minutes. PCR products
diluted 1:100 were analyzed on an ABI PRISM® 3130xl automatic sequencer
(Applied Biosystem, Foster City, CA). The molecular size of
microsatellite alleles was evaluated by using GeneMapper4.0. The
reliability of all microsatellites was tested for each locus in terms of
the presence of null alleles, the coefficient of inbreeding and the
deviation from Hardy-Weinberg equilibrium (HWE) using a Chi-square test
implemented in Micro-checker 2.2.3.

Two hypervariable domains of the mitochondrial control region (CR) were
used to investigate the genetic structure at the mitochondrial level. In
detail, the full control region of the mitochondrion was PCR-amplified
in two overlapping fragments of about 1200 bp, using the Platinum TAQ
kit (Invitrogen), according to the manufacturer's instructions. Primers
were developed using reference sequences from the mitochondrion
of\emph{M. myotis} (Table S2). The amplification protocol was as
follows: initial denaturation step at 94°C for 2 minutes; 40 cycles of
denaturation for 30 seconds, annealing at 51°C or 56°C for 30 seconds
respectively for PCR1 and 2, and extension at 72°C for 2 minutes; final
extension step at 72°C for 5 minutes. PCR products were sequenced on an
ABI PRISM® 3130xl genetic analyzer. Sequences were trimmed to obtain two
fragments of the hypervariable HVI and HVII domains. Haplotypes for the
concatenated HVI and HVII were inferred in MEGA 6.0 (Tamura, Stecher,
Peterson, Filipski, \& Kumar, 2013).

Genetic information obtained for the nuclear and mitochondrial DNA were
used to investigate the genetic population structure of \emph{M.
myotis}within South Tyrol. Analyses were carried out assuming each bat
belonged to a distinct population based on its roost of sampling. We
first determined the genetic variability existing within each separate
roost. In particular, we calculated allelic richness across loci (A) and
expected heterozygosity (H\textsubscript{E}) from microsatellites data
using GeneAlex, while the number of haplotypes (N), gene (h) and
nucleotide (\selectlanguage{greek}π\selectlanguage{english}) diversity of mitochondrial sequences were calculated in
Arlequin 2.0 (Castella et al., 2001; Ruedi et al., 2008). In addition,
we used MEGA 6 to determine mean nucleotidic distance between
individuals from different roosts based on the concatenated HVI and
HVII. We then assessed the genetic differentiation between populations
at both the nuclear and mitochondrial level, as expressed by the
fixation index (F\textsubscript{ST}) calculated using Genealex and
Arlequin 2.0 respectively. We considered little difference for
F\textsubscript{ST} values ranging from 0 to 0.05, moderate from 0.05 to
0.15 and great for values above 0.15 (Balloux \& Lugon-Moulin, 2002). We
tested the hypothesis of genetic isolation by distance (IBD) by plotting
linearized F\textsubscript{ST} values=F\textsubscript{ST}/(1-FS)
(Slatkin, 1995) against the ln(geographical distance) using a Mantel
test implemented in GeneAlex (Rousset, 1997). In particular, we used
geographical 2D distances calculated along the valleys' bottom rather
than Euclidean distances, as they are likely closer to real distances
covered by bats when flying.

For mitochondrial data only, we also investigated the phylogenetic
relationship between haplotypes through Maximum Likelihood (ML)
phylogenetic analyses implemented in PhyML 3.0 software using the
general time-reversible (GTR) model of nucleotide substitution with
gamma-distributed rate variation among sites (with four rate categories,
G4) and a heuristic SPR branch-swapping search (Dereeper et al., 2008).
One thousand bootstrap replications were performed to assess the
robustness of individual nodes. Mean nucleotide distance between and
within clades thus identified was calculated in MEGA 6 (Tamura et al.,
2013).

Phylogenetic relationship of South Tyrolean M. myotis with European
individuals based on mitochondrial haplotypes (HVII)

To investigate the phylogenetic relationship between South
Tyrolean\emph{M. myotis} and individuals from neighboring areas we used
sequences only from the HVII region of the mitochondrion, which has been
widely used throughout Europe (Bogdanowicz, Lesi\selectlanguage{polish}ń\selectlanguage{english}ski, Sadkowska-Todys,
Gajewska, \& Rutkowski, 2013; Bryja et al., 2010; Castella et al., 2001;
Furman et al., 2014; Ruedi \& Castella, 2003; Ruedi et al., 2008).
Sequences from this study were trimmed to include the sole HVII region
and were aligned with representative sequences of different haplotypes
reported in Europe for this bat species using Mafft with the G-INS-I
setting (Katoh, Misawa, Kuma, \& Miyata, 2002) (Table S3). Phylogenetic
relationship between individuals was determined using ML tree
implemented in PhyML 3.0 software using the general time-reversible
(GTR) model of nucleotide substitution with gamma-distributed rate
variation among sites (with four rate categories, G4), a heuristic SPR
branch-swapping search and 1000 bootstrap replications to assess the
robustness of individual nodes (Dereeper et al., 2008). To obtain the
best representation of the haplotype diversity in our study area,
phylogenetic analyses were run using all available samples, thus
including adult males and youngsters in their first year of age captured
during the reproductive season, either in May or September (Table 1).

Serology and statistical analyses

Blood samples were pre-diluted 1:30 and were analyzed for the presence
of antibodies against EBLV-1 using a modified Rapid Fluorescent Focus
Inhibition Test (RFFIT), in which EBLV-1b was used as challenge virus
(Leopardi et al., 2018; Serra-Cobo, Amengual, Carlos Abell\selectlanguage{ngerman}án, \& Bourhy,
2002). Samples were analyzed on a three-fold dilution basis and titers
were calculated through the Reed-Muench method and expressed as
LogD50/ml. Samples were considered positive when able to inhibit viral
growth at a minimum dilution of LogD50/ml \selectlanguage{english}[?]1.95.

We then tested how individual and environmental parameters influence
both the likelihood of being seropositive and the serological titer of
neutralizing antibodies against LYSVs in the target species \emph{M.
myotis.} In particular, the variables tested included geographic
(altitude and coordinates), seasonal (before and after the birth pulse),
demographic (age and sex) and genetic parameters (relative presence of
individuals showing haplotypes clustering to distinct clades, using as a
reference mitochondrial haplogroups defined by Ruedi et al, 2008). Full
statistical analyses are reported as supplemental material
(Supplementary Methods). Briefly, we applied a population averaged
models using Generalized Estimating Equations (GEE) and a linear mixed
model (LMM) to investigate the effects of all variables, respectively on
the likelihood of showing neutralizing antibodies and on their titer
(Dohoo, Wayne, \& Stryhn, 2009; Liang \& Zeger, 1986; West, Welch, \&
Galecki, 2007). For both types of models, we treated individuals sampled
within the same colony as a cluster, thus assuming that all observations
obtained within the same colony are correlated. Accordingly, we
performed a robust estimation of the variances of the regression
coefficients for the qualitative analysis and included a
random-intercept for colony in the LMM (Rao et al., 2014; Ying \& Liu,
2006). To assess the goodness of proposed models, we used the
Quasi-likelihood under the independence model Criterion (QIC) and the
Area under the ROC Curve (AUC) for GEE models, or the Akaike Information
Criterion (AIC) and residual analysis for LMM models (Dohoo et al.,
2009; Littell, Milliken, Stroup, Wolfinger, \& Oliver, 2006; Samur,
Coskunfirat, \& Saka, 2014) considering a p-value \textless{}0.05 as
significant.

\textbf{Results}

Description of colonies and samples

Five colonies of greater mouse-eared bats were investigated in South
Tyrol in 2016 (Figure 1). All colonies were located in the roof of
active churches and covered almost the whole region to the border with
Austria. The distance between colonies, calculated along bottom valleys
in order to reflect the real route of animals, ranged from 29.7 (roosts
one-three) to 125.8 kilometers (roosts three-four) (Figure 1). All
roosts hosted maternity colonies from late March to late September,
mostly including adult females with their offspring. Adult males were
sporadically sampled in all locations, particularly during the month of
September (Figure S1). All colonies hosted between 1000 and 2000
animals, with the exception of the northernmost site, where we only
found around 200 individuals (colony three, Figure 1). \emph{M.
myotis}was often the most abundant species within roosts. However,
co-roosting with the sibling species \emph{M. blythii} was confirmed in
all locations, especially during the mating season in September, when
the relative frequency of the two species widely differed between
colonies (Figure S2). In addition, a segregated aggregation of about 100
\emph{M. marginatus} was recorded within colony two in May.

Population genetic structure

Individual samples of \emph{M. myotis} suitable for genetic analyses
were 120 for the microsatellite analysis and 112 samples for the
mitochondrial analysis, as detailed in Table 1. Data were obtained from
25-30 female bats sampled in May from four out of five colonies, while
no more than nine samples were collected from colony three due to its
small size and scarce accessibility. In order to secure the robustness
of genetic analyses, we then run an additional set of tests using a
reduced dataset including only nine individuals for each colony. These
analyses showed consistent results with the main tests (Supplementary
Methods).

Among the 15 microsatellites markers published for \emph{M.
myotis}(Castella \& Ruedi, 2000), 12 were selected to carry out this
study as they i) could be successfully amplified in most samples, ii)
showed variability within the populations, iii) had no evidence for null
allele and iv) respected the Hardy Weinberg equilibrium (Table S1).
Genotyping of all individuals allowed for the detection of 109 distinct
alleles, with an overall mean of 9.5 alleles across loci, ranging from
6.83 to 10.58 within each of the investigated roost (Table 2). Genetic
analyses based on allele frequency for the 12 selected microsatellites
supported low genetic differentiation between different roosts
(F\textsubscript{ST} = 0.030, SE 0.006). Indeed, pairwise
F\textsubscript{ST} values between colonies ranged between 0.009 and
0.036 (mean 0.0193) and showed significant although little
differentiation only for the small colony three (p-value = 0.001) (Table
3). This same colony also showed the lowest mean allelic richness across
loci (Table 2).

Regarding genetic analyses on the mitochondrial DNA, we aligned
sequences of 413 bp, among which 20 sites were variable among the South
Tyrolean dataset, seven within the HVI and 13 within the HVII regions,
defining nine distinctive haplotypes included in two main clades (Figure
2, Table S4). Mean nucleotide distance was 0.12\% within groups and
4.5\% between groups. The most common haplotype was Hc\_01, found in
66\% of all individuals and in all colonies, with frequency ranging
between 41\% and 75\% in different locations. The overall frequency of
the other haplotypes varied between 0.9\% and 17\%, with five haplotypes
found in a single colony, one found in two colonies and two found in
four colonies (Table S4). In each colony, we found three to seven
distinct haplotypes, with colony two showing the highest variability
(n=7) and the highest number of private alleles (n=3) (Figure 3, Table
2, TableS4). Indeed, mean gene and nucleotide diversity confirmed to be
higher within this colony (Table 2). In turn, colony two showed the
highest mean nucleotide distance from other colonies based on sequences
from HVI+HVII (Table 3). Similarly to what was observed for
microsatellites, our data support a very limited geographical
structuring in the area, with F\textsubscript{ST} values ranging between
-0.013 and 0.084 (mean 0.02), and showing significant although low
differentiation only between colonies 1 and 2 (F\textsubscript{ST}:
0.084; p value: 0.019) (Table 3). The Mantel test detected a no sign for
isolation by distance based on either mitochondrial (R = 0.287,
p=0.052), or nuclear markers (R= 0.011, p=0.43) (Figure S3).

Phylogenetic analyses of M. myotis based on HVII sequences

Genetic sequences referring to the sole HVII domain of the mitochondrial
CR region belonged to 10 distinct haplotypes, among which six were newly
described and one was previously described in \emph{Myotis blythii} only
(Table S5).

Phylogenetic analyses that considered our haplotypes with the ones
already described across Europe showed they all clustered within
haplogroups A, B or C as described by Ruedi et al. (2008) (Figure 3).
Ninety-five percent of individuals showed haplotypes clustering within
haplogroup B, including the widespread haplotype H12 and six other
haplotypes described for the first time, named H-ST16-1/6. Four out of
six of these haplotypes were unique to a single colony, one was
exclusively found in an adult male, and one was found in two different
colonies and an adult male (Figure 3, Table S5). In addition, six
individuals from three colonies (4.1\%) shared the pan-European
haplotype H1, belonging to the haplogroup A. Finally two individuals
from two different colonies carried the genetic signature of haplogroup
C, previously found in North-Western Italy and Switzerland, among which
one haplotype was newly described and another one was previously
described from a \emph{M. blythii} . Crucially, both these individuals
were youngsters, so that they were not included in the determination of
the genetic structure.

Haplotypes belonging to more than one haplogroup were found in all
colonies, with the exception of the southern colony five, with
representatives from groups A, B and C described only in colony three,
much closer to the border compared to other colonies (Figure 3, Table
S5). Interestingly, adult males included in these analyses only carried
signatures belonging to haplogroup B (Figure 3, Table S5).

Circulation of rabies-related lyssaviruses

Serological analyses performed in 2016 showed neutralization of EBLV-1b
in 119 out of 270 (44\%) individual blood samples from South
Tyrolean\emph{M. myotis,} with serological titers ranging from 2 to 2.4
LogD50/ml (Table 4)\emph{.} In addition, 46 samples (17\%) from
different roosts and seasons showed viral inhibition below the
determined cutoff for the method. Observed sero-prevalence and specific
antibody titers increased after the birth pulse, occurring at the end of
May across the whole population (Table 4). Despite the percentage of
seropositive individuals varied from 0 to 26.5\% among colonies in early
May, the seasonal increasing trend was confirmed in all colonies (Table
4, Figure 4). Overall, animals under 1 year of age showed a higher
percentage of positivity and higher titers compared to adults; however,
this result might be confounded by the fact that we found only few adult
animals in September, when sero-prevalence has been proven considerably
higher in all colonies (Table 4, Figure S1). Indeed, taking into account
the correlation among bats within the same colony, results from
multivariable analyses suggest that the influence of seasonality alone
might explain the qualitative (QIC=173.1630, AUC=90.57) and quantitative
(AIC=-104.9) serological pattern found in the dataset (Supplementary
methods). Overall, these analyses confirmed the higher probability to
find sero-positive bats in autumn as compared to spring (94.17\% vs
9.55\%), also showing a mean significantly higher serological titer
(2.32 vs 2.11 LogD50/ml) (Table 5, Figure 5) and regardless of the age
category. Indeed, we found no significant difference in serological
titers between youngsters and adults in September (Figure 5).

\textbf{Discussion}

This study describes the combined use of population genetics and
serological analyses to investigate the infection dynamics of a
rabies-related lyssavirus (RRLV) in the greater mouse-eared bat in South
Tyrol, the northernmost region in Italy. In particular, serological
tests were specifically directed towards EBLV-1, even if the circulation
of a highly related virus cannot be completely ruled out due to the lack
of virus identification in this study and, more in general, in this
species.

In this context, our aim was to define the spread of EBLV-1 (or its
related RRLV) in the area and to interpret serological data from
different locations using the connectivity between roosts derived from
genetic analyses as a proximate measure for the likelihood of viral
transmission. In addition, phylogenetic analyses were performed to
address the possible movement of individuals across the Alps, which
could be related with the dispersal of lyssaviruses that, despite being
widely circulating in Europe, have never been described in Italy
(Leopardi et al., 2018; Shipley et al., 2019). Our study has focused on
maternity roosts, which are easier to locate compared to groups of adult
males, and provide higher chances for virus amplification as a
consequence of a bigger colony size, more frequent and closer
interactions among individuals and due to the yearly replenish of
susceptible individuals after the birth pulse (Drexler et al., 2011).

The detection of antibodies against EBLV-1 in South Tyrolean maternity
colonies of greater mouse-eared bats dates back to 2012, despite no
mortality has ever been related to LYSV circulation so far (Leopardi et
al., 2018). The presence of antibodies in healthy bat colonies is
peculiar in the ecology of LYSVs, and has been extensively described
elsewhere (Amengual, Bourhy, Lopez-Roig, \& Serra-Cobo, 2007; David T S
Hayman et al., 2010; Robardet et al., 2017; Suu-Ire et al., 2017).
Indeed, LYSVs are widely known for their pathogenicity in non-flying
mammals, invariably lethal when symptoms develop (Fisher et al., 2018).
In this study, we confirmed that all the investigated colonies are
exposed to the virus, as they show highly specific neutralizing
antibodies. Antibody titer were lower compared to other mammals; similar
pattern has been already described in bats for other pathogens, both in
the field and after experimental infection, and might be related with
the high efficiency of their innate, non-antibody-mediated pathway for
viral control (Baker, Schountz, \& Wang, 2013). In addition, we detected
a significant variation of sero-positivity across a single reproductive
season, supporting seasonal variation in the circulation of LYSVs in all
the locations investigated and, overall, an increasing sero-prevalence
in late summer compared to spring. These data are consistent with
similar findings in \emph{Myotis} and serotine bats (Amengual et al.,
2007; Robardet et al., 2017; Serra-Cobo et al., 2013), and could relate
to an increased virus transmission after the birth pulse, as suggested
for other viruses as a consequence of the large uptake of susceptible
individuals (Drexler et al., 2011). Indeed, higher antibody titers were
found during late summer, which could be a sign of seroconversion due to
viral exposure. This result differs from recent evidences determined for
EBLV-2 in \emph{Myotis daubentonii,} for which it was suggested a peak
in virus transmission later during the autumnal swarming, when males and
females aggregate for mating (Horton et al., 2020). However, this is
rather predictable, considering that bats are highly variable in their
ecology, so that differences in life history traits including
hibernation, colony formation, parturition and mating are likely to
determine peculiarities in virus dynamics as well (D. T S Hayman et al.,
2013). Despite peaks in transmission might depend upon host ecology,
most species follow strict seasonal patterns which might affect
prevalence of viruses (D. T S Hayman et al., 2013); thus, we suggest
that comparison between data of sero-prevalence detected from different
years or locations should always account for differences in the sampling
period. In this context, 100\% peak of sero-prevalence recorded in this
study is exceptional compared to previous evidences in the same host
species (Amengual et al., 2007; Schatz et al., 2014; Serra-Cobo et al.,
2002; \selectlanguage{polish}Š\selectlanguage{english}imi\selectlanguage{polish}ć \selectlanguage{english}et al., 2018) and is likely related to a very late sampling,
when adults were already dispersing for mating. In addition, it is wise
to consider to what extent the strong effect of seasonality might hide
the influence of other factors, including the geographical,
demographical or climatic data. Indeed, although preliminary analyses
suggested that the youngest animals were more likely to be serologically
positive compared to adults, the effect of age lost significance when
accounting for the dependence on seasonality. This is likely related to
non-homogeneous sampling across age classes of different sampling
campaigns.

None of the five roosts investigated was more likely to be infected,
suggesting that EBLV-1 or a related cross-reacting virus is circulating
across the area with no geographical restriction. Indeed, genetic data
derived from South Tyrolean \emph{Myotis myotis} are consistent with a
single meta-colony, with movement of individuals between colonies likely
favoring viral transmission. Despite several studies already documented
regional panmixia of \emph{M. myotis} at the nuclear level, we also
found lack of structuring based on mitochondrial DNA, strengthening the
hypothesis that population across the whole South Tyrol are highly
connected. In addition, F\textsubscript{ST} values inferred from nuclear
and mitochondrial markers were similar, suggesting a much lower
philopatric behaviour than previously described in Germany, France and
Switzerland despite a similar spatial scale (Castella et al., 2001;
Petri, P\selectlanguage{ngerman}ääbo, Von Haeseler, \& Tautz, 1997), and supporting regular
movements of individuals between colonies, similarly to what observed in
the serotine bat (\emph{Eptesicus serotinus} ) (Moussy et al., 2015).
The potential use of several roosts in the area was also supported by
occasional recapture in the big colony two of adult females which were
tagged elsewhere, despite a structured capture-recapture study has still
to be performed to quantify inter-colonial movements. Interestingly,
colony two showed the highest diversity in the area, also supporting the
mixing of bats in this spot, characterized by the biggest population
size and by a central position within the study area. However, such a
higher diversity might also be explained by the historical aggregation
of bats in this territory from different colonies already existing in
neighbouring zones; indeed, the church was completed only in the early
19\textsuperscript{th} century, well after the remaining roosts included
in the study.

A meta-population structure for \emph{Myotis myotis} is described here
for the first time, providing critical information to unravel dynamics
of LYSVs in this bat species. Indeed, previous mathematical models
suggested this bat was unable to sustain the circulation of EBLV-1
alone, supporting that sero-positivity in the Balearic Islands was
likely associated with inter-species transmission from the highly vagile
species \emph{Miniopterus scheibersii} (Colombi et al., 2019;
Pons-Salort et al., 2014)\emph{.} In South Tyrol, the greater
mouse-eared bats form very large maternity colonies within churches,
where the interaction with other species is strongly limited compared to
the cave dwelling populations typical of the Mediterranean area. In the
area target of our study, colonies mostly consist of \emph{M.
myotis,}with \emph{M. blythii} being sporadically found throughout the
season and a small population of \emph{M. emarginatus} recorded in a
single roost from May to July. No co-roosting with \emph{Miniopterus
schreibersii} have ever been recorded in the studied colonies (Drescher,
2004). However, the yearly detection of seropositive individuals highly
supports maintenance of the virus within the population (Leopardi et
al., 2018). In this context, the meta-population structure seen in our
sampling area as opposed to the close population model in the Balearic
Islands could explain virus maintenance in \emph{M. myotis} even in the
absence of \emph{M. schreibersii} . Indeed, several studies suggest that
the exchange of individuals between roosts may be one of the main
factors favoring the persistence of viruses across the whole population,
sometimes allowing for local fade out of infection with subsequent
reintroduction (Blackwood, Streicker, Altizer, \& Rohani, 2013; Colombi
et al., 2019; Horton et al., 2020; Pons-Salort et al., 2014).

Despite being largely described across Europe, EBLV-1 has never been
detected in Italy (Leopardi et al., 2018; Shipley et al., 2019). Indeed,
the large majority of individuals included in our sample carried a
mitochondrial signature typical of the Italian peninsula, confirming the
Alps as major barrier for bats, including \emph{M. myotis} (Ruedi \&
Castella, 2003; Ruedi et al., 2008). However, our data also confirmed
that individuals belonging to the major European clade A and to the
clade C, previously reported only across the border between Switzerland
and North-Western Italy, are present in South Tyrol, suggesting that
transboundary admixture of animals is possible. Indeed, haplotypes from
all three clades were found in the small colony three, located just on
the border with Austria, which also showed a weak but significant sign
of nuclear fixation. While it is possible that these results are due to
continental individuals reaching this location during dispersal,
coexistence of several divergent matrilines in this population may also
result from the persistence of ancestral polymorphism during
coalescence. As colony three is located in the oldest church in the
area, dating back to 1337, it is likely that the current genetic pattern
is shaped by both present- time and recent- past demographic events.
Either way, these data support that South Tyrolean valleys might act as
narrow corridors across the Alps, allowing for the movement of
individuals from the north. In particular, the dispersal of bats across
the Alps could either provide or have provided in the recent past a
corridor for the introduction of LYSVs from continental Europe, where
they are widespread. Regarding EBLV-1, the origin of the current lineage
has been dated back to 1400 (Troupin et al., 2017), so that introduction
in Italy could be related to both ongoing or recent admixture of animals
from South Tyrol and other northern areas, where the virus has been
confirmed virologically. The spread of viruses across the home range of
bat populations has already been described for other pathogens,
including lyssaviruses, henipaviruses, coronaviruses and astroviruses
(Halczok et al., 2017; Leopardi et al., 2016; Olival et al., 2020; Peel,
Sargan, et al., 2013). Unfortunately, the lack of viral characterization
in this bat species prevented us to compare the geographical structuring
of LYSVs and \emph{Myotis myotis} , which could help to explain the role
of this bat in the dispersal and evolution of EBLV-1 (Carver \& Lunn,
2020; Olival et al., 2020). Challenges in the detection of bat viruses
are not peculiar to our study or to LYSVs, but are likely related with
low prevalence and short shedding period of viruses in these animals
and, more generally, in wildlife (Wilkinson \& Hayman, 2017). In this
context, antibodies are easier to detect and persist longer, so that
serology is widely used as a proxy for virus circulation in wildlife to
model mechanisms of virus persistence within bat population even prior
to virus detection (Gilbert et al., 2013; Peel, McKinley, et al., 2013).

Regarding the genetic approach used in this study, we were able to
amplify 12 microsatellites described by Castella et al., (2001), and
developed a new protocol for the amplification of the complete control
region of the mitochondrion. This included sequencing of two
hypervariable regions (HVI and HVII), which were successfully amplified
and concatenated from most samples. Compared to previous studies which
had used the sole HVII, the additional presence of the HVI fragment
allowed to identify a higher variability, suggesting that our approach
might have a slightly better resolution for genetic analyses. South
Tyrolean \emph{Myotis} bats showed variability in all but one
microsatellite (C113), confirming results already obtained by Berthier
et al (Berthier, Excoffier, \& Ruedi, 2006). In general, mean diversity
within colonies was similar to what has already been described in other
studies, both at the nuclear and mitochondrial levels (Castella et al.,
2001, 2000; Ruedi \& Castella, 2003; Ruedi et al., 2008). Our analyses
showed more heterogeneity for the parameter ``nucleotide diversity''
compared to the ``gene diversity'' calculated within different colonies,
ranging between 0.001 to 0.013 and from 0.431 to 0.783, respectively
(Table 2). Indeed, gene diversity only considers the number of detected
haplotypes while the nucleotide diversity also takes into account the
degree of their divergence. Thus, the ten-fold higher nucleotide
diversity in colonies two and three is likely related to the admixture
of haplotypes that belong to different phylogenetic clades, as shown in
other studies (Castella et al., 2001; Ruedi \& Castella, 2003; Ruedi et
al., 2008). Similarly to other studies, we determined genetic
structuring of \emph{M. myotis} based on both nuclear and mitochondrial
markers, in order to test for female philopatry, which is generally
supported for this species (Castella et al., 2001). However, we found
comparable results from microsatellites and mitochondrial sequences,
thus disproving the expected pattern in our sample. These unexpected
results could be either related to peculiar ecology of South Tyrolean
populations or to lower spatial scale compared to other studies on the
same species.

In conclusion, we provide serological evidence for the circulation of a
RRLV in the South Tyrolean population of \emph{M. myotis,} antigenically
related to EBLV-1. Unlike the Mediterranean populations, \emph{M.
myotis} in northern Italy is a strictly house dwelling species, where
adult females aggregate in church roofs between April and September to
form large maternity colonies reaching over 2000 individuals, with a
remarkable chance for human encroachment (Zahn, 1999). As all LYSVs can
cause clinical rabies in humans, this study has a strong impact on
public health, regardless of the viral species actually circulating in
the study area. Fortunately, we founded a strong seasonal pattern,
suggesting the highest risk for human exposure might be limited in time,
easily predictable and likely associated with animal birth. In this
context, preventive measures to limit human exposure by limiting access
to the colony during most critical times could be beneficial to both
humans and animals, which is imperative considering the ecological
importance of this endangered species.

Genetic data supported animal movements between colonies, potentially
favoring viral dispersal across the host population home range and
likely allowing for viral maintenance in the area. In addition, genetic
data from this study provide important information on the ecology of the
species, suggesting that females might be more faithful to the natal
area rather than to the natal roost. Besides being crucial to inform
epidemiological modeling for disease dynamics, these results have
relevant implications for the conservation of this endangered species,
suggesting for example that monitoring and protection should be
performed at the regional rather than local level, as animal movements
between roosts might confound fluctuations in colony sizes.

\textbf{Acknowledgments}

The authors want to acknowledge Eric Petit and Francesca Ellero for
reviewing a first draft of the work, Paola Bonato and Nicola Ferrè for
support on the geographic information system (GIS) and Eva Ladurner,
Christian Drescher and Sara Ciullo for the technical and logistical
support in animal sampling.

\textbf{Fundings}

This research was supported by the Italian Ministry of Health (WFR
GR-2011-023505919 and RC IZSVe-08-2018) and by the and by the European
Commission through FP7, project PREDEMICS (Grant agreement no 278433).

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\textbf{Data Accessibility}

All sequences for the entire Control Region of the mitochondrion
generated for the study are available in Genbank, with accessions
MT254225 - MT254403. Specimen level data including species, sampling
location (coordinates), sex, age class, microsatellite genotypes, and
extrapolated sequences for HVI and HVII of the mitochondrion are
available at Dryad (dataset to be deposited).

\textbf{Author Contributions}

Stefania Leopardi: research design, fieldwork, laboratory and
computational analyses, paper writing

Marzia Mancin: research design, statistical analyses, paper writing

Barbara Zecchin, Angela Salomoni and Bianca Zecchin: laboratory analyses

Pamela Priori: fieldwork

Dino Scaravelli: research design and fieldwork

Paola De Benedictis: funding, research design and coordination, review
of the manuscript

\textsuperscript{}\textbf{Tables}

\textbf{Table 1. Sample size for serological and genetic analyses used
during the study.}\selectlanguage{english}
\begin{longtable}[]{@{}llllll@{}}
\toprule
\textbf{Colony} & \textbf{Nuclear Variability} & \textbf{Nuclear
Variability} & \textbf{Mitochondrial variability} &
\textbf{Mitochondrial variability} & \textbf{Mitochondrial
variability}\tabularnewline
\midrule
\endhead
& \textbf{A\textsuperscript{1}} &
\textbf{H\textsubscript{E}\textsuperscript{2}} &
\textbf{N\textsuperscript{3}} & \textbf{h\textsuperscript{4}} &
\selectlanguage{greek}\textbf{π\textsuperscript{5}}\selectlanguage{english}\tabularnewline
1 & 10.58 (0.84) & 0.81 (0.02) & 4 & 0.431 +/- 0.109 & 0.006 +/-
0.002\tabularnewline
2 & 10.00 (0.88) & 0.80 (0.03) & 7 & 0.783 +/- 0.065 & 0.013 +/-
0.004\tabularnewline
3 & 6.83 (0.63) & 0.75 (0.03) & 3 & 0.555 +/- 0.165 & 0.011 +/-
0.003\tabularnewline
4 & 10.17 (0.88) & 0.80 (0.03) & 3 & 0.467 +/- 0.087 & 0.001 +/-
0.001\tabularnewline
5 & 9.50 (0.87) & 0.79 (0.03) & 3 & 0.435 +/- 0.111 & 0.001 +/-
0.001\tabularnewline
\bottomrule
\end{longtable}

The number is based on the total of \emph{M. myotis} sampled from each
colony, as \emph{M. blythii} were excluded from these
analyses.\textsuperscript{1}AM: Number of adult males included in the
sample.

\textbf{Table 2: Genetic variability of colonies under study}

\textsuperscript{1}Allelic richness, \textsuperscript{2}expected
heterozygosity across microsatellite loci; \textsuperscript{3}Number of
haplotypes, \textsuperscript{4}gene diversity
and\textsuperscript{6}nucleotide diversity based on the concatenated
HVI+HVII fragments of the mitochondrion's control region, calculated
using the T92 model for nucleotide substitution. The standard error is
indicated between brackets. Standard deviation is indicated as +/-.

\textbf{Table 3} . \textbf{Pairwise differentiation between colonies}\selectlanguage{english}
\begin{longtable}[]{@{}llllllll@{}}
\toprule
\begin{minipage}[b]{0.10\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[b]{0.10\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[b]{0.10\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[b]{0.10\columnwidth}\raggedright\strut
\textbf{1}\strut
\end{minipage} & \begin{minipage}[b]{0.10\columnwidth}\raggedright\strut
\textbf{2}\strut
\end{minipage} & \begin{minipage}[b]{0.10\columnwidth}\raggedright\strut
\textbf{3}\strut
\end{minipage} & \begin{minipage}[b]{0.10\columnwidth}\raggedright\strut
\textbf{4}\strut
\end{minipage} & \begin{minipage}[b]{0.10\columnwidth}\raggedright\strut
\textbf{5}\strut
\end{minipage}\tabularnewline
\midrule
\endhead
\begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
\textbf{Nuclear DNA}\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
\textbf{F\textsubscript{ST}}\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
\textbf{1}\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
0.293\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
0.002\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
0.348\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
0.243\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\textbf{2}\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
0.010\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
0.001\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
0.095\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
0.119\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\textbf{3}\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
0.029*\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
0.036*\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
0.001\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
0.001\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\textbf{4}\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
0.009\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
0.011\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
0.033*\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
0.137\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\textbf{5}\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
0.010\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
0.011\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
0.033*\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
0.011\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
\textbf{Mitochondrial DNA}\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
\textbf{F\textsubscript{ST}}\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
\textbf{1}\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
0.019\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
0.309\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
0.332\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
0.615\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\textbf{2}\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
0.084*\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
0.273\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
0.070\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
0.061\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\textbf{3}\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
0.008\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
0.019\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
0.285\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
0.455\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\textbf{4}\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
0.002\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
0.050\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
0.022\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
0.825\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\textbf{5}\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
-0.013\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
0.064\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
-0.007\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
-0.033\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\textbf{nucleotidic distance}\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\textbf{1}\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
0.002\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
0.002\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
0.001\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
0.001\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\textbf{2}\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
0.010\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
0.002\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
0.002\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
0.002\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\textbf{3}\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
0.008\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
0.011\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
0.001\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
0.001\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\textbf{4}\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
0.004\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
0.008\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
0.006\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
0.001\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\textbf{5}\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
0.004\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
0.008\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
0.006\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
0.001\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\strut
\end{minipage}\tabularnewline
\bottomrule
\end{longtable}

Values for nuclear and mitochondrial pairwise fixation index
(F\textsubscript{ST} - Wright, 1951) between individuals of different
roosts are shown below the diagonal with the associated p-value (based
on 1000 permutations) indicated above the diagonal. Significant values
are marked with*. Nuclear indexes are based on analyses of 12
microsatellites. Mitochondrial indexes are calculated using sequences of
concatenated HVI and HVII fragments. Between colonies mean nuclear
distance is indicated below the diagonal as calculated with MEGA 6 using
T92 model of nucleotide substitution with the standard error indicated
above the diagonal.

\textbf{Table 4. Serological analyses based on the RFFIT test against
EBLV-1}\selectlanguage{english}
\begin{longtable}[]{@{}llllllll@{}}
\toprule
\begin{minipage}[b]{0.12\columnwidth}\raggedright\strut
\textbf{Month}\strut
\end{minipage} & \begin{minipage}[b]{0.12\columnwidth}\raggedright\strut
\textbf{Roost}\strut
\end{minipage} & \begin{minipage}[b]{0.12\columnwidth}\raggedright\strut
\textbf{Observed seroprevalence (+/n) \textsuperscript{1}}\strut
\end{minipage} & \begin{minipage}[b]{0.12\columnwidth}\raggedright\strut
\textbf{titer (mean)} \textbf{(LogD50/ml)}\strut
\end{minipage} & \begin{minipage}[b]{0.12\columnwidth}\raggedright\strut
\textbf{Dubious (n)\textsuperscript{2}}\strut
\end{minipage} & \begin{minipage}[b]{0.12\columnwidth}\raggedright\strut
\textbf{AF} \textbf{{[}+/n (\%){]}}\strut
\end{minipage} & \begin{minipage}[b]{0.12\columnwidth}\raggedright\strut
\textbf{Y} \textbf{{[}+/n (\%){]}}\strut
\end{minipage} & \begin{minipage}[b]{0.12\columnwidth}\raggedright\strut
\textbf{AM} \textbf{{[}+/n (\%){]}}\strut
\end{minipage}\tabularnewline
\midrule
\endhead
\begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
May\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
1\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
26.5 (9/34)\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
2.1\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
12\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
9/34 (26.5)\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
2\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
10.3 (6/58)\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
2.1\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
12\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
5/50 (10)\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
0/1\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
1/7 (14.3)\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
3\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\textless{}25\% (0/8)\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
4\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
0/7\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
0/1\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
4\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\textless{}10\% (0/33)\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
5\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
0/32\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
0/1\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
5\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
7.1 (2/28)\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
2\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
6\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
2/21 (9.5)\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
0/3\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
0/4\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
mean\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
10.5 (17/161)\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
2.06\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
Sept\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
1\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
100 (9/9)\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
2.3\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
3/3 (100)\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
4/4 (100)\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
2/2 (100)\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
2\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
100 (42/42)\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
2.3\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
4/4 (100)\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
33/33 (100)\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
5/5 (100)\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
3\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
100 (3/3)\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
2.3\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
1/1 (100)\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
2/2 (100)\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
4\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
84.6 (22/26)\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
2.3\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
4\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
7/9 (77.8)\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
7/7 (100)\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
8/10 (80)\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
5\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
89.7 (26/29)\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
2.4\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
3\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
3/3 (100)\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
22/24 (91.7)\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
2/2 (100)\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
mean\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
93.5 (102/109)\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
2.32\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
Overall\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
Overall\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
44 (11/270)\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
2.22\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
46\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
33/163 (20.2)\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
67/75 (89.3)\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
20/32 (62)\strut
\end{minipage}\tabularnewline
\bottomrule
\end{longtable}

\textsuperscript{1}In case of negative results for all samples, we
indicated the prevalence as below the limit of detection as calculated
based on the sampling size in relation to the size of the colony.

\textsuperscript{2}Number of samples showing signs of virus inhibition
between 40-50\%, which is below the cutoff value for the determination
of titer. AF: adult females; Y: animals below 1 year of age; AM: adult
males

\textbf{Table 5: Mean values for the seasonal prevalence and titre of
antibodies against LYSVs predicted from GEE and LMM models.}

season

Predicted sero-prevalence

\emph{Error}

Lower

Upper

\emph{spring}

\emph{0.09551}

\emph{0.04306}

\emph{0.03823}

\emph{0.2190}

\emph{autumn}

\emph{0.9417}

\emph{0.03535}

\emph{0.8206}

\emph{0.9828}

season

Predicted mean antibody titre

Error

Lower

Upper

spring

2.1106

0.03682

2.0376

2.1835

autumn

2.3235

0.01658

2.2907

2.3563



\textbf{Figures}

\textbf{Figure 1. Geographical location of maternity colonies of\emph{M.
Myotis} included in the study}\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image1/image1}

\end{center}
\end{figure}

The location of each roost investigated during 2016 in South Tyrol is
shown as a yellow circle within the map, numbered from one to five as
indicated throughout the text. Possible routes taken by bats to move
between colonies are shown in red, determined along the valley's
bottoms. The map was created using European Digital Elevation Model
version 1.1 under the framework of the Copernicus program.

\textbf{Figure 2. Phylogenetic relationship between haplotypes
identified for the concatenated HVI-HVII.}\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image2/image2}

\end{center}
\end{figure}

A maximum of five sequences for haplotypes have been used to build ML
tree using phyML. Boostrap values above 70 are shown in the tree. The
figure shows 9 haplotypes, denoted as Hc 1-9, grouped in two main
clades, indicated as grey (B) and black (A) continuous lines. The
distribution of each haplotype between the five colonies under study is
shown as a pie chart, in which colonies are represented in blue (1), red
(2), green (3), grey (4) and black (5). The total number of individuals
corresponding to each haplotype is indicated as a bar chart beside the
tree.

\textbf{Figure 3.Phylogenetic analyses based on the HVII of the
mitochondrial CR.}\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image3/image3}

\end{center}
\end{figure}

Sequences are classified in Haplogroups according to Ruedi et al (2008)
shown with different colors maintained across panels A-C (A: blu;
B:orange;C: green; D:red; E:light blu; F: violet; G:yellow). Panel A: ML
Phylogenetic tree customized using iToll. Sequences from this studies
are shown using different symbols according to sample location, as
indicated in the table. Adult males are shown as check signs. Panel B.
distribution of hlotypes in Europe, according to this study and data the
literature (Bogdanowicz et al., 2013; Bryja et al., 2010; Castella et
al., 2001; Furman et al., 2014; Ruedi et al., 2008; Ruedi and Castella,
2003). Panel C: Zoom of haplotypes described in the study area and
bordering ones.

\textbf{Figure 4. Distribution of the observed sero-prevalence in
different colonies according to the sampling season}\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image4/image4}

\end{center}
\end{figure}



\textbf{Figure 5. Distribution of antibodies titer for season and for
age in autumn}

\textbf{}\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/Screen-Shot-2020-04-04-at-2-22-23-PM/Screen-Shot-2020-04-04-at-2-22-23-PM}

\end{center}
\end{figure}\selectlanguage{english}
\begin{longtable}[]{@{}ll@{}}
\toprule
&\tabularnewline
\bottomrule
\end{longtable}

\selectlanguage{english}
\FloatBarrier
\end{document}

