Manfredi Di Lorenzo
email: manfredi.dilorenzo@libero.it

Paolo Guidetti

Antonio Di Franco

Antonio Calò

Joachim Claudet

Assessing spillover from Marine Protected Areas and its drivers: a meta-analytical approach Running title: Spillover from marine protected areas

Keywords: Coastal, coral reefs, temperate reef, fully protected areas, no-take zone, marine reserve, fish, small-scale fisheries

The ocean offers vital ecosystem services to mankind. However, human activities, especially overfishing, may seriously impact fish populations and ecosystems. Fully protected areas (FPAs) are an effective tool for biodiversity conservation and can sustain local fisheries via spillover, i.e. the export of juvenile and adult individuals from FPAs outwards. Yet, whether or not spillover is a general phenomenon following the establishment and effective management of an FPA is still controversial. Here, we developed a meta-analysis of a unique global database covering 23 FPAs in 12 countries, including both published literature and specifically collected field data, to assess the capacity of FPAs to export biomass and whether this response was mediated by specific FPA features (e.g. size, age) or species characteristics (e.g. mobility, economic value). Results, on average, show that fish biomass and abundance outside FPAs are higher: i) in locations close to FPA borders (<200m) than in locations further away (>200m); ii) for species with a high commercial value; iii) in the presence of a partially protected area (PPA) surrounding the FPA.

Spillover slightly increased as FPAs are larger and older and as species are more mobile. Our work grounds on the broadest dataset compiled to date on marine species ecological spillover beyond FPAs' borders and highlights elements that could enhance local fishery management.

INTRODUCTION

Human activities are leading to dramatic modifications of the ocean [START_REF] Mccauley | Marine defaunation: Animal loss in the global ocean[END_REF] and overfishing is among the most damaging stressors on marine biodiversity [START_REF] Ipbes | Summary for policymakers of the global assessment report on biodiversity and ecosystem services of the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services[END_REF]. However, fisheries, especially small scale fisheries, are valuable economic activities, often vital for food security and poverty alleviation, and sources of livelihood with strong socio-cultural implications in coastal areas worldwide [START_REF] Cisneros-Montemayor | A Global Estimate of Seafood Consumption by Coastal Indigenous Peoples[END_REF].

There is, therefore, an urgent need to identify management strategies able to reconcile conservation and fisheries goals by both protecting marine biodiversity and enhancing fishing yields/revenues [START_REF] Gaines | Evolving science of marine reserves: new developments and emerging research frontiers[END_REF][START_REF] Jupiter | A Social-Ecological Systems Approach to Assessing Conservation and Fisheries Outcomes in Fijian Locally Managed Marine Areas[END_REF].

Although marine protected areas (MPAs) are widely recognized as an important tool for biodiversity conservation [START_REF] Claudet | Marine reserves: size and age do matter[END_REF][START_REF] Edgar | Global conservation outcomes depend on marine protected areas with five key features[END_REF][START_REF] Giakoumi | Ecological effects of full and partial protection in the crowded Mediterranean Sea: A regional meta-analysis[END_REF] and fisheries management [START_REF] Abesamis | Gradients of abundance of fish across no-take marine reserve boundaries: evidence from Philippine coral reefs[END_REF][START_REF] Goñi | Spillover from six western Mediterranean marine protected areas: evidence from artisanal fisheries[END_REF][START_REF] Russ | Enhanced biodiversity beyond marine reserve boundaries: the cup spillith over[END_REF], how ubiquitous are fishery benefits delivered by MPAs is still largely debated [START_REF] Hilborn | Marine biodiversity needs more than protection[END_REF][START_REF] Kerwath | Marine protected area improves yield without disadvantaging fishers[END_REF][START_REF] Sale | Critical science gaps impede use of no-take fishery reserves[END_REF]. There is a body of evidence suggesting that FPAs can play an important role for fisheries management, especially for SSF [START_REF] Franco | Five key attributes can increase marine protected areas performance for small-scale fisheries management[END_REF][START_REF] Januchowski-Hartley | Spillover of fish naïveté from marine reserves[END_REF][START_REF] Russ | Enhanced biodiversity beyond marine reserve boundaries: the cup spillith over[END_REF]. Two ecological processes can drive fishery benefits of FPAs: population replenishment through larval subsidies [START_REF] Manel | Long-Distance Bene fi ts of Marine Reserves : Myth or Reality[END_REF][START_REF] Marshall | Underestimating the benefits of marine protected areas for the replenishment of fished populations[END_REF] and the spillover of fish biomass from protected areas to surrounding fishing grounds (Rowley 1994). While both processes require populations to firstly recover within the boundaries of the FPAs, generally the former is key to the long-term persistence of exploited populations also at relatively large distance from the MPA (i.e. hundreds of kms, [START_REF] Manel | Long-Distance Bene fi ts of Marine Reserves : Myth or Reality[END_REF], while the latter produces faster benefits to fisheries mainly across shorter distances [START_REF] Halpern | Spillover from marine reserves and the replenishment of fished stocks[END_REF]. The spatio-temporal scale of these two processes is species-specific [START_REF] Green | Larval dispersal and movement patterns of coral reef fishes, and implications for marine reserve network design[END_REF][START_REF] Mccauley | Marine defaunation: Animal loss in the global ocean[END_REF].

The occurrence and magnitude of spillover is variable and context-dependent (Di [START_REF] Lorenzo | Spillover from marine protected areas to adjacent fisheries has an ecological and a fishery component[END_REF]. The maximum distance from FPA borders at which spillover effects are still detectable is a crucial issue to better understand the spatial extent of FPA benefits to local fisheries. Most studies found that spillover occur on average at distances of about 200 m from FPAs' borders, and all agree that it does not exceed 1 km [START_REF] Abesamis | Gradients of abundance of fish across no-take marine reserve boundaries: evidence from Philippine coral reefs[END_REF][START_REF] Renee | Density-dependent spillover from a marine reserve : long-term evidence[END_REF][START_REF] Guidetti | Potential of marine reserves to cause community-wide changes beyond their boundaries[END_REF][START_REF] Halpern | Spillover from marine reserves and the replenishment of fished stocks[END_REF][START_REF] Marques | Spillover Effects of a Community-Managed Marine Reserve[END_REF][START_REF] Russ | Enhanced biodiversity beyond marine reserve boundaries: the cup spillith over[END_REF]. According to Di [START_REF] Lorenzo | Spillover from marine protected areas to adjacent fisheries has an ecological and a fishery component[END_REF], two types of spillover should be considered on the basis of their assessment: "ecological spillover" encompassing all forms of net emigration of juveniles, subadults and/or adults from the MPA outwards; "fishery spillover", i.e. the fraction of ecological spillover that can directly benefit fishery yields and revenues through the marine species biomass that can be fished [START_REF] Lorenzo | Spillover from marine protected areas to adjacent fisheries has an ecological and a fishery component[END_REF].

Spillover is not only important for local SSFs, but also for tourism-based blue economy.

More abundant and larger fish exported from FPAs (where scuba-diving is often forbidden) attract more divers, thus supporting the local economy [START_REF] Micheli | Achieving success under pressure in the conservation of intensely used coastal areas[END_REF][START_REF] Roncin | Uses of ecosystem services provided by MPAs: How much do they impact the local economy? A southern Europe perspective[END_REF].

The overall relative contribution of potential drivers of spillover is poorly known. Two main categories of drivers may affect spillover: (i) MPA features: age, design (e.g. size, shape, location), presence of PPAs, the level of enforcement, habitat continuity/discontinuity across FPA borders [START_REF] Goñi | Spillover from six western Mediterranean marine protected areas: evidence from artisanal fisheries[END_REF][START_REF] Harmelin-Vivien | Gradients of abundance and biomass across reserve boundaries in six Mediterranean marine protected areas: Evidence of fish spillover?[END_REF][START_REF] Kaunda-Arara | Out-migration of Tagged Fishes from Marine Reef National Parks to Fisheries in Coastal Kenya[END_REF][START_REF] Kay | Effects of marine reserves on California spiny lobster are robust and modified by fine-scale habitat features and distance from reserve borders[END_REF]; (ii) species characteristics: the species-specific ability to move across the FPA borders, related, e.g., to the intraspecific behaviour of individuals, habitat preferences and species mobility, fishing pressure [START_REF] Kaunda-Arara | Out-migration of Tagged Fishes from Marine Reef National Parks to Fisheries in Coastal Kenya[END_REF]. Some studies reported that spillover may require several years (>10 years) to take place after a FPA is established [START_REF] Abesamis | Gradients of abundance of fish across no-take marine reserve boundaries: evidence from Philippine coral reefs[END_REF][START_REF] Harmelin-Vivien | Gradients of abundance and biomass across reserve boundaries in six Mediterranean marine protected areas: Evidence of fish spillover?[END_REF][START_REF] Russ | Do marine reserves export adult fish biomass? Evidence from Apo Island , central Philippines[END_REF][START_REF] Russ | Spillover from marine reserves: the case of Naso vlamingii at Apo Island, the Philippines[END_REF], while others detected spillover after only a few years from FPA creation (< 5 years; [START_REF] Francini-Filho | Evidence for spillover of reef fishes from a no-take marine reserve: An evaluation using the before-after control-impact (BACI) approach[END_REF][START_REF] Guidetti | Potential of marine reserves to cause community-wide changes beyond their boundaries[END_REF]. Spillover has been observed from FPAs surrounded or not by a PPA [START_REF] Abesamis | Gradients of abundance of fish across no-take marine reserve boundaries: evidence from Philippine coral reefs[END_REF][START_REF] Francini-Filho | Evidence for spillover of reef fishes from a no-take marine reserve: An evaluation using the before-after control-impact (BACI) approach[END_REF][START_REF] Harmelin-Vivien | Gradients of abundance and biomass across reserve boundaries in six Mediterranean marine protected areas: Evidence of fish spillover?[END_REF][START_REF] Zeller | Movements of reef fishes across marine reserve boundaries : effects of manipulating a density gradient[END_REF] and detected both from small (< 1km 2 ; [START_REF] Abesamis | Gradients of abundance of fish across no-take marine reserve boundaries: evidence from Philippine coral reefs[END_REF]Harmelin-Vvivien et al., 2008;[START_REF] Russ | Do marine reserves export adult fish biomass? Evidence from Apo Island , central Philippines[END_REF][START_REF] Russ | Spillover from marine reserves: the case of Naso vlamingii at Apo Island, the Philippines[END_REF] and large FPAs [START_REF] Ashworth | Effects of fishing pressure and trophic group on abundance and spillover across boundaries of a no-take zone[END_REF][START_REF] Fisher | Changes in finfish community structure associated with an offshore fishery closed area on the Scotian Shelf[END_REF][START_REF] Stobart | Longterm and spillover effects of a marine protected area on an exploited fish community[END_REF]. Habitat continuity inside and outside the FPA is thought to facilitate spillover [START_REF] Renee | Density-dependent spillover from a marine reserve : long-term evidence[END_REF][START_REF] Kaunda-Arara | Out-migration of Tagged Fishes from Marine Reef National Parks to Fisheries in Coastal Kenya[END_REF], but several studies detected spillover also where the habitat was discontinuous across FPA borders [START_REF] Goñi | Spillover of spiny lobsters Palinurus elephas from a marine reserve to an adjoining fishery[END_REF][START_REF] Guidetti | Potential of marine reserves to cause community-wide changes beyond their boundaries[END_REF][START_REF] Harmelin-Vivien | Gradients of abundance and biomass across reserve boundaries in six Mediterranean marine protected areas: Evidence of fish spillover?[END_REF][START_REF] Kay | Effects of marine reserves on California spiny lobster are robust and modified by fine-scale habitat features and distance from reserve borders[END_REF]. Spillover is expected to occur mostly for relatively mobile species [START_REF] Buxton | When is spillover from marine reserves likely to benefit fisheries?[END_REF][START_REF] Halpern | Spillover from marine reserves and the replenishment of fished stocks[END_REF], but some studies showed that sedentary, [START_REF] Chapman | Gradients in coral reef fish density and size across the Barbados Marine Reserve boundary:effects of reserve protection and habitat characteristics[END_REF][START_REF] Eggleston | Disturbance-induced "spill-in" of Caribbean spiny lobster to marine reserves[END_REF][START_REF] Forcada | Effects of habitat on spillover from marine protected areas to artisanal fisheries[END_REF][START_REF] Goñi | Spillover from six western Mediterranean marine protected areas: evidence from artisanal fisheries[END_REF][START_REF] Goñi | Spillover of spiny lobsters Palinurus elephas from a marine reserve to an adjoining fishery[END_REF][START_REF] Zeller | Movements of reef fishes across marine reserve boundaries : effects of manipulating a density gradient[END_REF], vagile, [START_REF] Abesamis | Gradients of abundance of fish across no-take marine reserve boundaries: evidence from Philippine coral reefs[END_REF][START_REF] Forcada | Habitat continuity effects on gradients of fish biomass across marine protected area boundaries[END_REF][START_REF] Guidetti | Potential of marine reserves to cause community-wide changes beyond their boundaries[END_REF], and highly vagile species, [START_REF] Chapman | Gradients in coral reef fish density and size across the Barbados Marine Reserve boundary:effects of reserve protection and habitat characteristics[END_REF][START_REF] Kaunda-Arara | Out-migration of Tagged Fishes from Marine Reef National Parks to Fisheries in Coastal Kenya[END_REF][START_REF] Stobart | Longterm and spillover effects of a marine protected area on an exploited fish community[END_REF] may spillover beyond FPA borders.

Here, we performed a meta-analysis to 1) investigate the extent of spillover occurrence from FPAs globally and 2) assess which FPA features and species characteristics mainly drive spillover. To do so, we compiled the most complete global database on spillover, covering 23 FPAs in 12 countries, combining information from reviewed literature and data gathered through specific underwater visual census samplings on the field.

METHODS

Data collection

We assembled our dataset using two different approaches: extracting data from literature and performing ad hoc field activities to collect new data.

Articles on spillover from published peer-reviewed literature were collected through Web of Science back to 1994, when the term spillover was used for the first time (Rowley 1994). The following search string was used: ("spillover" OR "spill-over" OR "spill over") AND ("marine protected area*" OR "marine reserve*" OR "no-take zone*" OR "fisher* closure*" OR "fully protected area*"). It was decided to focus strictly on FPAs as this protection level is the more likely to produce spillover effects (Di Lorenzo et al., 2016 and references therein). Sixty-three studies of empirical assessments of spillover were found. They were either based on underwater visual census (UVC), catch or tagging abundance and/or biomass data. Spillover has been modelled in various ways in the literature, such as using linear gradients of abundance/biomass decline from FPA borders (e.g. [START_REF] Goñi | Spillover of spiny lobsters Palinurus elephas from a marine reserve to an adjoining fishery[END_REF][START_REF] Harmelin-Vivien | Gradients of abundance and biomass across reserve boundaries in six Mediterranean marine protected areas: Evidence of fish spillover?[END_REF] or tracking individual movements across FPA borders [START_REF] Afonso | Spatial patterns in reproductive traits of the temperate parrotfish Sparisoma cretense[END_REF][START_REF] Barrett | Rock lobster movement patterns and population structure within a Tasmanian Marine Protected Area inform fishery and conservation management[END_REF][START_REF] Follesa | Spillover effects of a Mediterranean marine protected area on the European spiny lobster Palinurus elephas (Fabricius, 1787) resource[END_REF][START_REF] Kay | Effects of marine reserves on California spiny lobster are robust and modified by fine-scale habitat features and distance from reserve borders[END_REF][START_REF] Kerwath | Marine protected area improves yield without disadvantaging fishers[END_REF]. In order to keep the maximum number of studies, we built a model of spillover that would be as inclusive as possible in terms of different measurements and ways to report the data. Data from papers were extracted either from tables or from graphs using ImageJ (http://imagej.nih.gov/ij). Contextual information about the FPAs was recorded from the articles and/or by contacting their authors: FPA age and size, whether the FPA was situated on an island or along a coastline, presence of PPA surrounding the FPA, and habitat continuity/discontinuity along FPA borders (Table 1). Information on species mobility (sedentary or vagile) and economic value (commercial, low commercial or not commercial) was also collected from the papers or FishBase (http://www.fishbase.org). It is worth noting that juveniles of target species were also included in the low commercial category as during that life stage they are not fishery targets.

To enhance the dataset, we conducted additional fieldwork in 13 FPAs in 6 countries. Data were gathered using underwater visual census (UVC). SCUBA diving was carried out on rocky substrates between 5 and 15 m deep, using 25x5 m strip transects parallel to the coast. Along each transect, the divers swam one way at constant speed, identifying all fishes encountered to the lowest taxonomic level possible and recording their number and size. Fish sizes were estimated visually in 2 cm increments of total length (TL) for most of the species, and within 5 cm size classes for large-sized species (i.e. with maximum size >50 cm). Fish biomass was estimated from size data by means of length-weight relationships from the available literature and existing databases. UVC replicates (from 6 to 12 transects) were carried out close and far from FPAs borders, according to the rationale we used to detect spillover (see section 2.2).

Only one study used fisheries yield to assess spillover. Due to the absence of replication we could not account for fisheries spillover and had to restrict our analysis on ecological spillover (REF). A total of 334 assessments from 23 [well enforced?] MPAs and 31 taxonomic groups (including species, genus or family) worldwide were finally used in the meta-analysis (Fig. 1; Table 1; Supplementary material Table S1).

Data analysis

A meta-analytical approach was used to investigate spillover occurrence and drivers in our database. We used as effect size the log-relative difference in mean fish abundance and biomass between locations close (<200 m) and far (>200 m) from the FPA borders. We set the threshold at 200 m according to the distance up to which spillover is generally observed in the literature [START_REF] Abesamis | Gradients of abundance of fish across no-take marine reserve boundaries: evidence from Philippine coral reefs[END_REF][START_REF] Guidetti | Potential of marine reserves to cause community-wide changes beyond their boundaries[END_REF][START_REF] Harmelin-Vivien | Gradients of abundance and biomass across reserve boundaries in six Mediterranean marine protected areas: Evidence of fish spillover?[END_REF][START_REF] Russ | Spillover from marine reserves: the case of Naso vlamingii at Apo Island, the Philippines[END_REF][START_REF] Russ | Enhanced biodiversity beyond marine reserve boundaries: the cup spillith over[END_REF]. This approach is conservative in the sense that it favours false negative (absence of detection of spillover if it occurs over larger spatial extents) over false positive (detection of spillover when it does not occur, or over spatial extents with no significance for [small scale] fisheries management).

We used a weighted mixed-effects meta-analysis [START_REF] Gurevitch | Statistical issues in ecological meta-analysis[END_REF] to quantify the magnitude of spillover and asses its drivers. Two different meta-analyses were done on abundance and biomass. For each study i, the spillover effect size R i of the studied species across the studied FPA was modelled as the natural logarithm response ratio [START_REF] Gurevitch | Statistical issues in ecological meta-analysis[END_REF][START_REF] Osenberg | Effect Size in Ecological Experiments: The Application of Biological Models in Meta-Analysis[END_REF] of the mean abundance or biomass measured within 200 meters (

) and over 200 meters ( ) from the FPA boundary:

The within-study variance v i associated to the effect sizes was calculated as follows:

where and are the standard deviations of and , respectively, and where and are the associated sample sizes.

All effect sizes were weighted, accounting for both the within-and among-study variance components [START_REF] Hedges | Fixed-and Random-Effects Models in Meta-Analysis[END_REF]. Models were fitted and heterogeneity tests were run to assess how MPA-level (FPA age and size, island or coastline FPA, presence of a PPA, habitat continuity/discontinuity along FPA borders) and species-level (mobility and economic) drivers could mediate spillover from FPAs (Table 1). All analyses were done in R (R Core Team 2016) and weighted mixed-effects model fitting and heterogeneity tests were carried out using the metaphor package [START_REF] Viechtbauer | Conducting Meta-Analyses in R with the metafor Package[END_REF].

RESULTS

Overall, we found 33% higher fish abundance and 54% higher biomass close to the FPA borders (<200m) compared to further away ( = 0.29 ± 0.15 95% CI and = 0.43 ± 0.21 95% CI, respectively), indicating the general occurrence of spillover. However, effect sizes were heterogeneous across assessments (Q T = 7314, df = 167, p < 0.001; Q T = 7777, df = 164, p < 0.001; respectively) (Supplementary material Table S2).

The presence of a PPA around FPAs played an important role. Spillover was observed more often from those FPAs surrounded by or next to a PPA (Figure 1). Abundance and biomass were respectively 37% and 84% higher closer to rather than further away from the FPA boundaries (Supplementary Materials Table S3).

For abundance data, spillover was mostly observed in FPAs established along coastlines rather than in FPAs surrounding a whole island (Figure 1). This difference was not observed when considering biomass data (Figure 1; Supplementary material: Table S2).

The occurrence and magnitude of spillover was only slightly affected by the age or the size of the FPA. Although statistically significant, the effect of age was marginal both for abundance ( = 0.008 ± 0.007 95% CI) and biomass ( = 0.014 ± 0.010 95% CI). The effect of the size of the FPA played a limited but detectable role only in the case of abundance ( = 0.04 ± 0.03 95% CI for abundance; = 0.02 ± 0.03 95% CI for biomass).

Habitat continuity/discontinuity across FPA borders did not seem to affect the occurrence of spillover, both for abundance (Q E =6767.35; df=165; p=0.0001) and biomass (Q E =7299.05; df=163; p=0.0001) (Figure 1).

Spillover density and biomass was detected either for sedentary or vagile species (Figure 1;

Supplementary Material: Table S1). Only species with high commercial value showed a spillover effect from FPA both in terms of abundance and biomass (Figure 1; Supplementary Material: Table S1).

DISCUSSION

Our results showed that spillover of marine species, both in terms of abundance and biomass, can be expected as a general response of FPAs. Based on the data that we have been able to gather, the present study focused on ecological spillover (sensu Di [START_REF] Lorenzo | Spillover from marine protected areas to adjacent fisheries has an ecological and a fishery component[END_REF]. We found only one study that assessed fisheries spillover (using yield as response variable), which precluded us to account for this component of spillover in our meta-analysis. More efforts should be directed towards assessing spillover through fish catches along gradients across MPA borders.

We showed that fish biomass and abundance outside FPAs are higher in locations close to FPA borders (<200m) than in locations further away (>200m), for species with a high commercial value, and that it is occurring more in the presence of a partially protected area (PPA) surrounding the FPA. Spillover slightly increased as FPAs are larger and older and as species are more mobile.

To the best of our knowledge this is the first study considering the presence of PPA as potential driver of spillover, as well as benthic habitat continuity. Our findings suggest that the presence of a PPA might help the net export of biomass through spillover (and consequently the detection of fish abundance and/or biomass in the water) from the FPA. However, it is crucial to highlight that these patterns can be affected/altered by the magnitude of fishing effort around FPAs (in PPAs or in unprotected areas, depending on MPA zonation scheme). Fishing the line, i.e.

fishers' tendency to fish close to the boundaries of FPAs [START_REF] Kellner | Fishing the line near marine reserves in single and multispecies fisheries[END_REF], is a recognized activity occurring around FPAs. In the absence of a PPA, fishery activities around FPAs' borders are not subject to strict spatially-explicit regulations beside the ones imposed by national and international laws, generally resulting in a higher concentration of the fishing effort close to the FPA borders [START_REF] Renee | Density-dependent spillover from a marine reserve : long-term evidence[END_REF][START_REF] Chapman | Gradients in coral reef fish density and size across the Barbados Marine Reserve boundary:effects of reserve protection and habitat characteristics[END_REF][START_REF] Davidson | Effects of marine reserve protection on spiny lobster (Jasus edwardsii) abundance and size at Tonga Island Marine Reserve, New Zealand[END_REF][START_REF] Follesa | Spillover effects of a Mediterranean marine protected area on the European spiny lobster Palinurus elephas (Fabricius, 1787) resource[END_REF][START_REF] Russ | Enhanced biodiversity beyond marine reserve boundaries: the cup spillith over[END_REF][START_REF] Stamoulis | A seascape approach to investigating fish spillover across a marine protected area boundary in Hawai'i[END_REF]. The detection of ecological spillover could be negatively impacted by fishing pressure in the fished areas, but high fishing effort can also concentrate within PPAs leading to negative consequences of fishing the line in terms of fisheries spillover (Figure 2) [START_REF] Kleiven | Fishing pressure impacts the abundance gradient of European lobsters across the borders of a newly established marine protected area[END_REF][START_REF] Zupan | Marine partially protected areas: drivers of ecological effectiveness[END_REF].

Our findings can shed light on the results observed in a recent global meta-analysis assessing the ecological effectiveness of different levels of protection in partially protected aeas [START_REF] Zupan | How good is your marine protected area at curbing threats?[END_REF]. While the authors observed that fully and highly protected MPAs (sensu Horta e Cosat et al. 2016) harbour higher fish abundance and biomass that surrounding unprotected areas, they found that moderately protected areas are effective only when adjacent to a fully protected area. A possible explanation can thus be that in the absence of a fully protected area providing spillover, such moderately protected areas allow too much fishing activities to be effective. Spillover can thus be an important component driving the effectiveness of multi-zoned MPAs, allowing combinations of protection levels favouring both conservation and fishing access in partially protected area concentrating fishing [START_REF] Zupan | How good is your marine protected area at curbing threats?[END_REF].

We observed a slightly influence of time since protection (i.e. MPA age) on ecological spillover, in agreement with what has been observed for the response to protection within the FPA boundaries [START_REF] Claudet | Marine reserves: size and age do matter[END_REF][START_REF] Edgar | Global conservation outcomes depend on marine protected areas with five key features[END_REF][START_REF] Molloy | Effects of marine reserve age on fish populations: a global meta-analysis[END_REF]. This can be due to the fact that our synthesis included FPAs with a large variation in age (min=6 years, median=19 years, max=32 years).

The fact that only species with a high commercial value display spillover is not surprising as they are the ones responding more favorably to protection [START_REF] Kerwath | Marine protected area improves yield without disadvantaging fishers[END_REF] hence the ones most likely exporting adults from the FPA boundaries. According to [START_REF] Halpern | Spillover from marine reserves and the replenishment of fished stocks[END_REF], highly valued species are often the ones mostly targeted by extractive activities. For this reason, these are also the species responding most favourably and most rapidly to MPA establishment [START_REF] Claudet | Assessing the effects of marine protected area (MPA) on a reef fish assemblage in a northwestern Mediterranean marine reserve: Identifying community-based indicators[END_REF][START_REF] Babcock | Decadal trends in marine reserves reveal differential rates of change in direct and indirect effects[END_REF][START_REF] Kerwath | Marine protected area improves yield without disadvantaging fishers[END_REF]. An important difference between our synthesis and that by [START_REF] Halpern | Spillover from marine reserves and the replenishment of fished stocks[END_REF] is that while their study focussed on highly valued fish species only, our analysis, for the first time, integrated data of three commercial value categories of species (i.e. no value, low and high).

Differently to Halpern et al 2010, a slightly effect of FPA size on spillover was also found; it suggests that the set of MPAs included in our study cover a range of sizes representing a trade-off between the inclusion of the home ranges of most species and the optimal size for spillover to neighbouring areas [START_REF] Franco | Linking home ranges to protected area size: The case study of the Mediterranean Sea[END_REF][START_REF] Weeks | Using reef fish movement to inform marine reserve design[END_REF]. In fact, the size of a FPA should include the full home ranges of the protected species to obtain high conservation benefits [START_REF] Franco | Linking home ranges to protected area size: The case study of the Mediterranean Sea[END_REF][START_REF] Weeks | Using reef fish movement to inform marine reserve design[END_REF].

While several experimental studies have shown that habitat continuity between inside and outside FPAs may play a role in facilitating spillover [START_REF] Forcada | Habitat continuity effects on gradients of fish biomass across marine protected area boundaries[END_REF][START_REF] Goñi | Spillover from six western Mediterranean marine protected areas: evidence from artisanal fisheries[END_REF][START_REF] Halpern | Spillover from marine reserves and the replenishment of fished stocks[END_REF][START_REF] Kaunda-Arara | Out-migration of Tagged Fishes from Marine Reef National Parks to Fisheries in Coastal Kenya[END_REF], our meta-analysis showed that spillover could occur where the habitat across FPA borders is either homogeneous or heterogeneous. Such studies refer to the landscape connectivity theory ("the degree to which the landscape facilitates or impedes movement among resource patches"; [START_REF] Taylor | Connectivity is a vital element of landscape structure[END_REF], suggesting that similar habitat types across FPAs and fished areas may enhance the borders permeability [START_REF] Bartholomew | Influence of marine reserve size and boundary length on the initial response of exploited reef fishes in the Florida Keys National Marine Sanctuary[END_REF].

However, our results suggest that the likelihood that fish cross a different habitat rather than the preferred one also depends on how fish can perceive and respond behaviourally to integrate the patched habitat to minimize overall costs [START_REF] Bélisle | Measuring landscape connectivity: The challenge of behavioral landscape ecology[END_REF][START_REF] Wiens | Landscape ecology as a foundation for sustainable conservation[END_REF]. Therefore, although different habitats outside FPAs could be a barrier to fish movements (due e.g. to the increased risk of predation), individuals may be able to move beyond FPA borders most likely when a threshold level of population density/biomass (i.e. competition for local resources such as preys and refuges) is exceeded.

Here, we observed evidence of spillover for species regardless of their mobility In agreement with previous findings [START_REF] Halpern | Spillover from marine reserves and the replenishment of fished stocks[END_REF], we observed that species, regardless of their mobility, are able to perform spillover. Contrary to [START_REF] Halpern | Spillover from marine reserves and the replenishment of fished stocks[END_REF] we decided to use only sedentary and vagile species in our analysis and removed the highly vagile species. The fact that any species with different mobility levels can display spillover may support the use of FPAs for coastal, SSF management, as these fisheries are multi-specific and usually target both sedentary and mobile species [START_REF] Claudet | ECOLOGY -Ecological effects of marine protected areas: functioning[END_REF].

As in any qualitative review or quantitative synthesis or meta-analysis our study can harbour a publication bias. As studies evidencing spillover could be more likely published than those where no spillover is observed this would translate in some overestimation of spillover.

However, our sample covers a large array of species, MPA types, and biogeographic regions and is well representative of spillover assessment in marine protection worldwide. Besides, the way we modelled spillover can in fact have led to underestimations. We are thus quite confident that MPAs, through spillover and larval subsidies [START_REF] Marshall | Underestimating the benefits of marine protected areas for the replenishment of fished populations[END_REF], can play a significant role in replenishing surrounding areas, therefore enhancing fisheries and non-extractive activities that may benefit from increased fish density and biomass (e.g. scuba diving and tourism more in general).

In terms of socio-economic implications, therefore, the potential benefits induced by spillover could raise expectations in stakeholders (e.g. fishers, divers, tourists) that if shattered could induce a negative attitude and finally reduce support toward conservation initiatives and potentially foster non-compliant behaviours (e.g. poaching) [START_REF] Bergseth | Measuring and monitoring compliance in no-take marine reserves[END_REF]. In our study we use a conservative approach to assess spillover occurrence (i.e. spillover might have been underestimated in some cases), and in addition we point out the circumstances under which spillover could occur, which is more appropriate from a management point of view as deception can be dramatic when a management tool is oversold [START_REF] Chaigneau | Challenging the win-win discourse on conservation and development: Analyzing support for marine protected areas[END_REF][START_REF] Hogg | Interpretations of MPA winners and losers: a case study of the Cabo De Palos-Islas Hormigas Fisheries Reserve[END_REF]. This can allow to deliver a clear message to stakeholders and avoid overselling the occurrence of spillover, preventing unrealistic expectations, and contributing to foster support to conservation initiatives [START_REF] Bennett | Local support for conservation is associated with perceptions of good governance, social impacts, and ecological effectiveness[END_REF]).

Our findings highlight under which conditions spillover may be expected, allowing MPA managers and policy-makers to develop sound management strategies to eventually maximise the exploitation of fishable biomass exported by FPAs. In fact, contrary to FPAs for which wellestablished regulations of human activities have been identified to reach conservation goals (essentially no extractive activities allowed), proven conditions for PPAs effectiveness are still scarce (in terms of which activities to allow and to which limits) (Zupan et al., 2018). Globally PPAs include a variety of management measures that range from almost unprotected areas (with no regulations implemented) to virtually FPA (Zupan et al. 2018). From this perspective, an effort should be made to assess under which conditions PPAs can benefit local communities within a multiple-use MPA. As PPAs currently lack a consistent and well-designed set of regulations worldwide (Horta e Costa et al., 2016), MPAs, mainly aimed to maximize fishery benefits, should assess the fisheries yield within PPAs and fished areas integrated with integrated with fishing effort data in order to optimise spillover (Figure 2).

Figure 1 :

 1 Figure1: MPA-level and species-level drivers of spillover. The spillover indicator is the logtransformed ratio of fish biomass or abundance between close and far from fully protected area boundaries (average weighted effect size +/-95% CI). Green dots indicate effect sizes that do not overlap zero and red dots those that overlap zero. Heter.: Heterogeneous; Homog.: Homogeneous

Figure 2 :

 2 Figure 2: This generic conceptual framework illustrates the potential effects of presence and absence of partially protected area (PPA) surrounding fully protected area (FPA) on spillover. Three different scenarios are shown: A) high fishing pressure could reduce the ecological and fishery spillover assessment in fished area around FPA; B) high fishing pressure could reduce the ecological (standing stock biomass) and fishery (catches) spillover assessment within PPA surrounding the FPA and nullifies both spillover assessment in fished area; C) low fishing pressure could increase the ecological and fishery spillover assessment within PPA surrounding the FPA and enhances ecological and fishery spillover assessment in the fished area

Table 1 . Empirical studies and data that met the section criteria of our meta-analysis. For further details, see the supplementary material.

 1

	N/A: Data Not Available
				Presence of a
	Fully protected area name (Country)	Years since enforcement	Reserve Size (km 2 )	partially protected area	Number of species	Source
				(PPA)
						Russ and Alcala 1996; Russ et al. 2003,
	Apo (Philppines)	16	0.11	No	1	2004; Abesamis and Russ 2005; Abesamis
						et al 2006; Russ and Alcala 2011
	Asinara (Italy)	9	2.45	Yes	17	data collection
	Balicasag (Philppines)	16	0.08	No	1	Abesamis et al 2006
	Barbados (Caribbean)	15	2.3	No	Assemblage	Chapman and Kramer 1999
	Bonifacio (France)	19	0.74	Yes	13	data collection
	Cabo de Palos (Spain)	23	2.68	Yes	18	data collection
	Cabrera (Spain)	22	0.85	Yes	Assemblage	Harmelin Vivien et al 2008; Bellier et al 2013
	Cap Roux (France)	15	0.44	No	12	data collection
	Capo Carbonara (Italy)	6	0.6	Yes	16	data collection
	Channel Islands (California)	7	N/A	No	1	Kay et al 2012a
	Columbretes (Spain)	12	44	No	1	Goni et al 2006
	Cote Bleue (France)	32	0.85	No	12	data collection
	Egadi (Italy)	27	6.63	Yes	13	data collection
	Mombasa (Kenya)	6	10	No	Assemblage	McClanahan and Mangi 2000
	Portofino (Italy)	19	0.18	Yes	15	data collection
	Pupukea-Waimea (Hawaii)	17	0.71	No	Assemblage	Stamoulis and Friedlander 2013
	Strunjan (Slovenia)	10	0.46	Yes	7	data collection
	Su Pallosu (Italy)	11	4	No	1	Follesa et al 2011
	Tabarca (Spain)	20	14	Yes	1	Forcada 2008
	Telascica (Croatia)	30	0.12	Yes	13	data collection
	Tonga (Tonga)	7	18.35	No	1	Davidson et al. 2002
	Torre Guaceto (Italy)	18	1.38	Yes	12	Guidetti et al. 2007; data collection
	Zakyntos (Greece)	19	8	Yes	10	data collection

ACKNOWLEDGEMENTS

We wish to thank N. Barrett, C. Bené, J. Bohnsack, E. Brunio, R. Cole, R. Davidson, D. Eggleston, R. Francini-Filho, D. Freeman, E. Hardman, F.A. Januchowski-Hartley, M. Kay, S. Kerwath,. D.L. Kramer, D. Malone, R. Ormond, M. Readdie, C. Roberts, A. Tewfik, K. Turgeon, M. Young, C. Wilcox and D. Zeller for sharing information about habitat types across MPAs borders. The authors would like to thank Prof. Paul Hart, and the two anonymous referees for their constructive comments and their kind help in improving the manuscript. We are grateful to Dr. Katie Hogg for her suggestions and editing of the English of the MS. MDL was supported by a "Luigi and Francesca Brusarosco" grant. FishMPAblue2 project (Interreg Mediterranean programme), Italian Marine Strategy monitoring, Foundation de France (INTHENSE), the ERA-Net BiodivERsA (BUFFER) and the Agence Nationale de la Recherche (ANR-14-CE03-0001-01) for the Prince Albert II of Monaco Foundation (FPAII, Monaco) and the Total Corporate Foundation (France) financial support. Moreover, we are very grateful to all of MPAs directors and staff for their determining logistic and field support.

CONFLICT OF INTEREST:

The authors declare that they have no conflict of interest.


Marie Bidart

Isabelle Bonnet

Aurélie Hennebique

Zine Eddine Kherraf

Hervé Pelloux

François Berger

Muriel Cornet

Sébastien Bailly

Danièle Maubon
email: dmaubon@chu-grenoble.fr

Bidart-Coutton Marie

Berger François

C Inconspicua

C Guillermondii

An In-House Assay Is Superior to Sepsityper for Direct Matrix-Assisted Laser Desorption Ionization-Time of Flight (MALDI-TOF) Mass Spectrometry Identification of Yeast Species in Blood Cultures

scientifiques de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

Prompt, appropriate, first-line antifungal treatment has been shown to improve outcome in patients with fungemia, but identification is currently delayed by the need for subculture from positive blood cultures [START_REF] Puig-Asensio | Prospective Population Study on Candidemia in Spain (CANDIPOP) Project, Hospital Infection Study Group (GEIH), Medical Mycology Study Group (GEMICOMED) of the Spanish[END_REF][START_REF] Puig-Asensio | Epidemiology and predictive factors for early and late mortality in Candida bloodstream infections: a population-based surveillance in Spain[END_REF]. Mass spectrometry techniques based on MALDI-TOF technology have made it possible to identify species directly from positive blood cultures [START_REF] Posteraro | MALDI-TOF mass spectrometry in the clinical mycology laboratory: identification of fungi and beyond[END_REF]. The sample contains human cells, and identification protocols must lyse these cells efficiently (without disrupting the microorganism) and eliminate the unwanted human proteins. In-house protocols based on the lytic agent saponin have been described for bacterial identification [START_REF] Martiny | Comparison of an in-house method and the commercial Sepsityper TM kit for bacterial identification directly from positive blood culture broths by matrix-assisted laser desorption-ionisation time-of-flight mass spectrometry[END_REF][START_REF] Meex | Direct identification of bacteria from BacT/ALERT anaerobic positive blood cultures by MALDI-TOF MS: MALDI Sepsityper kit versus an in-house saponin method for bacterial extraction[END_REF], but only few assays have been developed for yeast-positive blood cultures [START_REF] Marinach-Patrice | Rapid species diagnosis for invasive candidiasis using mass spectrometry[END_REF][START_REF] Ferroni | Real-Time identification of bacteria and Candida species in positive blood culture broths by Matrix-Assisted Laser Desorption Ionization-Time of Flight Mass spectrometry[END_REF][START_REF] Ferreira | Microorganisms direct identification from blood culture by matrix-assisted laser desorption/ionization time-offlight mass spectrometry: Blood culture pathogens direct identification by MALDI-TOF[END_REF][START_REF] Spanu | Direct MALDI-TOF mass spectrometry assay of blood culture broths for rapid identification of Candida species causing bloodstream infections: an observational study in two large microbiology laboratories[END_REF]. Bruker produces an easy-to-use kit, Sepsityper®, which has yielded good results for the characterization of both bacteria and yeasts [START_REF] Buchan | Comparison of the MALDI Biotyper system using sepsityper specimen processing to routine microbiological methods for identification of bacteria from positive blood culture bottles[END_REF][START_REF] Yan | Improved identification of yeast species directly from positive blood culture media by combining Sepsityper specimen processing and Microflex analysis with the matrix-assisted laser desorption ionization Biotyper system[END_REF]. However, this commercial test has never been compared, for yeast identification, with any in-house protocol. We developed an in-house protocol for the direct identification, by MALDI-TOF, of the yeast species commonly isolated from blood cultures. We compared the results obtained with our assay to those obtained with Sepsityper®.

We used an artificial blood culture protocol (blood from healthy volunteers), to facilitate the testing of large numbers of strains and species [START_REF] Fricker-Hidalgo | Use of the BACTEC 9240 system with Mycosis-IC/F blood culture bottles for detection of fungemia[END_REF]. We used 61 strains previously identified by MALDI-TOF and representative of 12 species commonly implicated in fungemia: Candida albicans (15), C. glabrata [START_REF] Spanu | Direct MALDI-TOF mass spectrometry assay of blood culture broths for rapid identification of Candida species causing bloodstream infections: an observational study in two large microbiology laboratories[END_REF], C. parapsilosis [START_REF] Ferroni | Real-Time identification of bacteria and Candida species in positive blood culture broths by Matrix-Assisted Laser Desorption Ionization-Time of Flight Mass spectrometry[END_REF], C. kefyr [START_REF] Marinach-Patrice | Rapid species diagnosis for invasive candidiasis using mass spectrometry[END_REF], C. krusei [START_REF] Marinach-Patrice | Rapid species diagnosis for invasive candidiasis using mass spectrometry[END_REF], C. tropicalis [START_REF] Ferroni | Real-Time identification of bacteria and Candida species in positive blood culture broths by Matrix-Assisted Laser Desorption Ionization-Time of Flight Mass spectrometry[END_REF], Cryptococcus neoformans (4), C. dubliniensis (3), C. utilis (1), C. guillermondii (1), C. inconspicua [START_REF] Puig-Asensio | Prospective Population Study on Candidemia in Spain (CANDIPOP) Project, Hospital Infection Study Group (GEIH), Medical Mycology Study Group (GEMICOMED) of the Spanish[END_REF], and Saccharomyces cerevisiae [START_REF] Puig-Asensio | Prospective Population Study on Candidemia in Spain (CANDIPOP) Project, Hospital Infection Study Group (GEIH), Medical Mycology Study Group (GEMICOMED) of the Spanish[END_REF]. Six were isolated directly from blood cultures from patients. The strains were used to inoculate (10 yeast cells/flask) Mycosis IC/F and BACTEC Plus Aerobic/F or BACTEC plus Anaerobic/ F (C. glabrata only) flasks, and were incubated in BACTEC FX (Becton Dickinson) until the flask tested positive for their presence. Each positive flask was subjected to MALDI-TOF MS identification with a Microflex TM MALDI-TOF mass spectrometer (Bruker Daltonics, Germany). We first compared the following agents: 0.8% saponin (as described in ref ( 4)), 1% Triton, 1.8% SDS (two other commonly used lytic agents) and the Sepsityper® kit, on 17 strains. Two washing steps were included after lysis, because the inclusion of an additional washing step had been shown to improve identification scores ((11) and data not shown). Briefly, the lytic agent was added to 1 ml of medium from each positive flask, which was then vortexed and pelleted (16,000 RCF, two minutes). The supernatant was discarded and the pellet was washed twice in sterile distilled water (saponin, Triton and SDS1.8 protocol) or Sepsityper® washing buffer. It was then homogenized with an appropriate quantity of formic acid (from 2 µl to 15 µl, depending on pellet volume; mean of 5 µl) and an equal volume of acetonitrile was added. Following a final centrifugation (16,000 RCF, 2 min) 1 µl of supernatant was dispensed, in duplicate, on a polished steel target and covered with 1 µl α-cyano-4-hydroxycinnamic acid (HCCA) for MALDI-TOF analysis. The spectra obtained were analyzed with the BioTyper 2.0 database (Bruker Daltonics). The thresholds for interpretation were adapted as previously suggested [START_REF] Ferreira | Microorganisms direct identification from blood culture by matrix-assisted laser desorption/ionization time-offlight mass spectrometry: Blood culture pathogens direct identification by MALDI-TOF[END_REF][START_REF] Scola | Direct Identification of bacteria in positive blood culture bottles by Matrix-Assisted Laser Desorption Ionisation Time-of-Flight mass spectrometry[END_REF][START_REF] Idelevich | Rapid Identification and susceptibility testing of Candida spp. from positive blood cultures by combination of direct MALDI-TOF mass spectrometry and direct inoculation of Vitek 2[END_REF].

Identification scores were classified into four categories

: A [>2]; B [1.7-2]; C [1.4-1.7],
with the expected species proposed first and four times in a row; D [< 1.4] or not identified. The first three categories yielded acceptable results for identification to species level. In total, 305 tests were carried out (Table 1). According to our adapted scores, 95/107 (88.8%), 94/115 (81.7%), 16/42 (38%), 12/41 (29.2%) tests led to correct identification for the SDS1.8, Sepsityper®, saponin and Triton protocols, respectively. Protocols based on saponin and Triton were the least efficient for yeast identification in blood cultures, possibly because they lysed human cells less efficiently, leading to a mixed (yeast and human) and, thus, less specific spectrum profile. The spectrum obtained with the SDS1.8 protocol was very similar to that obtained with the Sepsityper® kit (Figure 1). Based on these results, we limited subsequent comparisons to the Sepsityper® and SDS1.8 protocols.

We analyzed 44 strains grown in both Mycosis IC/F and BACTEC Plus/F flasks with the SDS1.8 and Sepsityper® protocols (176 tests). Scores are reported as median values (interquartile range). Score was transformed into a qualitative value, with four classes corresponding to the identification categories (see above). The Wilcoxon signed rank sum test and Spearman's rank correlation analysis were used for quantitative scores and Fisher's exact test was used for qualitative scores. The results obtained with the two protocols were well correlated (Spearman's correlation coefficient r=0.70 p<0.001).

Median score was significantly higher with the SDS protocol (1.9 [1.7; 2.1]) than with Sepsityper® (1.8 [1.55; 2.0]) (Wilcoxon test p=0.003). This difference remained significant if separate analyses were carried out by vial type (Mycosis IC/F p<0.001 and BACTEC Plus p=0.04) (figure 2) and for the non-Candida albicans yeasts (C. albicans: p=0.16; non-C. albicans yeasts: p<0.001) (data not shown). A subgroup analysis by vial type showed that score class results were also better for the SDS assay than for the Sepsityper® assay for Mycosis IC/F (p=0.04) (Figure 3). This is the first comparison of an in-house protocol with the Sepsityper® kit for the MALDI-TOF identification of yeasts in positive blood cultures. We found that lysis with 1.8% SDS was globally superior to the Sepsityper® kit, particularly for yeasts isolated from Mycosis IC/F medium and for non-albicans species of Candida. The two protocols had similar durations (30 minutes), but the SDS1.8 protocol was cheaper than the Sepsityper® protocol (by a factor of 220: €0.025 vs. €5.5 euros per test). The SDS protocol yielded a correct identification rate of 100% (mean score 2 ± 0.19) in clinical practice, in tests on nine flasks from six patients, but a prospective study is required to confirm this performance in other vials containing patient's blood. As the 0.8% saponin procedure gave poorer results than previously reported for bacteria, rapid identification procedures for positive blood cultures will probably need to be adapted according to the results of direct examination. The SDS1.8 protocol appears to be an effective, cheap alternative for yeast identification in positive blood cultures.

Figure 1

 1 Figure 1 Spectral profile obtained for Candida krusei isolated from Mycosis® blood

Figure 2 :

 2 Figure 2: A. Boxplots of scores by protocol: **median score is significantly higher with

Figure 3 :

 3 Figure 3: Diagram showing the distribution of identification score classes, by protocol

Figure 5 :Figure 6 :

 56 Figure 5: A. Boxplots of scores by protocol: **median score is significantly higher with the SDS protocol than with Sepsityper® (p = 0.003). B. Boxplots of scores by protocols and type of blood culture flasks: * significant difference between the two protocols for BACTEC Plus (p=0.04) and **significant difference between the two protocols for Mycosis IC/F (p<0.001).

Table 1 : Detailed results for each species and each protocol. SEP: Sepsityper®, SDS: 1.8% SDS, SAP: 0.8% saponin, TRI: 1% Triton. M= Mycosis® media, B: bacterial media, NI= not identified.

 1

	SPECIES	C. albicans				C. glabrata			C. parapsilosis			C. kefyr				C. krusei
	PROTOCOL	SEP	SDS	SAP	TRI	SEP	SDS	SAP	TRI	SEP	SDS	SAP	TRI	SEP	SDS	SAP	TRI	SEP	SDS
	FLASKS	M B	M

Acknowledgments

Authors have no conflict of interest to declare


Aurélie Hennebique

Fabienne Gas

Hélène Batina

Cécilia De Araujo

Karine Bizet

Max Maurin
email: mmaurin@chu-grenoble.fr

Prof M Maurin

Evaluation of the Biotoxis qPCR detection® kit for Francisella tularensis detection in clinical

à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

INTRODUCTION

Francisella tularensis is a small Gram-negative bacterium causing the zoonotic disease tularemia [START_REF] Sjöstedt | Tularemia: history, epidemiology, pathogen physiology, and clinical manifestations[END_REF][START_REF] Maurin | Tularaemia: clinical aspects in Europe[END_REF]. More strictly, among the four subspecies of F. tularensis, only two are currently associated with human and animal tularemia cases: F. tularensis subsp. tularensis (Type A strains), in North America, and F. tularensis subsp. holarctica (Type B strains) in the whole northern hemisphere and southern Australia [START_REF] Sjöstedt | Tularemia: history, epidemiology, pathogen physiology, and clinical manifestations[END_REF][START_REF] Maurin | Tularaemia: clinical aspects in Europe[END_REF][START_REF] Jackson | Francisella tularensis subspecies holarctica, Tasmania, Australia, 2011[END_REF]. F. tularensis subsp. mediasiatica has been detected in arthropods and rodents in central Asia and Russia (1) but never associated with human infections. F. tularensis subsp. novicida (also referred to as F. novicida) is an aquatic bacterium, rarely responsible for opportunistic human diseases [START_REF] Hennebique | Tularemia as a waterborne disease: a review[END_REF].

Other aquatic Francisella species have been formerly or recently described, including F. philomiragia, another rare opportunistic human pathogen [START_REF] Hennebique | Tularemia as a waterborne disease: a review[END_REF].

F. tularensis can infect a wide range of vertebrate species (especially lagomorphs and small rodents) and arthropods (including Ixodidae ticks and mosquitoes) [START_REF] Sjöstedt | Tularemia: history, epidemiology, pathogen physiology, and clinical manifestations[END_REF][START_REF] Maurin | Tularaemia: clinical aspects in Europe[END_REF]. This bacterium is also able to survive for prolonged periods in the hydro-telluric environment [START_REF] Sjöstedt | Tularemia: history, epidemiology, pathogen physiology, and clinical manifestations[END_REF][START_REF] Maurin | Tularaemia: clinical aspects in Europe[END_REF][START_REF] Hennebique | Tularemia as a waterborne disease: a review[END_REF]. F. tularensis can contaminate humans through contact with infected animals, arthropod bites, exposure to contaminated environments, or ingestion of contaminated food or water [START_REF] Sjöstedt | Tularemia: history, epidemiology, pathogen physiology, and clinical manifestations[END_REF][START_REF] Maurin | Tularaemia: clinical aspects in Europe[END_REF]. Several clinical forms of tularemia exists, mainly depending on the portal of entry of the bacteria. The ulceroglandular and glandular forms correspond to localized lymphadenopathy, respectively, with or without a skin ulcer. The oropharyngeal form combines pharyngitis and cervical lymphadenopathy. The oculoglandular form usually corresponds to conjunctivitis with periauricular lymphadenopathy. The pneumonic form (pneumonia or pleuropneumonia) usually occurs through the inhalation of contaminated aerosols. The typhoidal form is severe sepsis, often with confusion, but with no inoculation lesion or lymphadenopathy [START_REF] Sjöstedt | Tularemia: history, epidemiology, pathogen physiology, and clinical manifestations[END_REF][START_REF] Maurin | Tularaemia: clinical aspects in Europe[END_REF].

Because of its ability to be spread by aerosols, its low infectious dose, and high virulence, F. tularensis is classified as a category A of potential biological threat agents by the US Centers for Disease Control and Prevention (CDC) [START_REF] Dennis | Tularemia as a biological weapon: medical and public health management[END_REF]. Pneumonic tularemia cases caused by the most virulent Type A strains are associated with up to 30% mortality rates [START_REF] Sjöstedt | Tularemia: history, epidemiology, pathogen physiology, and clinical manifestations[END_REF][START_REF] Maurin | Tularaemia: clinical aspects in Europe[END_REF][START_REF] Dennis | Tularemia as a biological weapon: medical and public health management[END_REF].

Tularemia diagnosis is currently based on serological methods, and F. tularensis detection by culture or PCR-based methods [START_REF] Maurin | Tularaemia: clinical aspects in Europe[END_REF]. However, this fastidious and slow-growing bacterium is usually isolated in less than 10% of tularemia patients [START_REF] Maurin | Tularaemia: clinical aspects in Europe[END_REF]. Serological methods can detect significant antibody titers only 2 to 3 weeks after disease onset [START_REF] Maurin | Tularaemia: clinical aspects in Europe[END_REF][START_REF] Yanes | Evaluation of In-House and Commercial Serological Tests for Diagnosis of Human Tularemia[END_REF]. Therefore, real-time PCR tests are currently the most effective method for detecting F. tularensis in human, animal, or environmental samples [START_REF] Maurin | Tularaemia: clinical aspects in Europe[END_REF]. Although many in-house qPCR tests have been developed, a friendly commercial test allowing rapid, accurate, and standardized detection of F. tularensis in various types of samples is a high priority.

The Biotoxis qPCR detection ® kit is a plate format TaqMan probe-based real-time PCR assay designed for the combined detection of B. anthracis, Y. pestis, and F. tularensis DNA in various sample types. In the present study, we evaluated this kit's performance for detection and identification of F. tularensis in DNA extracts from bacterial strains, clinical samples, and environmental water samples, in comparison to previously validated PCR tests used routinely in our laboratory.

MATERIALS AND METHODS

Biotoxis qPCR assay

The Biotoxis qPCR detection ® kit (Bertin Bioreagent, Montigny-le-Bretonneux, France) was carried out according to the manufacturer's instructions. Briefly, each of the PCR mixtures (25 µl) contained 12.5 µl of the qPCR mix, 3.75 µl of primers and probes mix, 3.75 µl of water, and 5 µl of DNA sample (at variable concentration according to sample type, see below). The PCR was performed on a Lightcycler ® 480 instrument II (Roche) with an initial enzyme activation step of 95°C for 3 min, followed by 45 cycles of denaturation at 95°C for 15 sec, and annealing and extension at 60°C for 30 sec. The results were analyzed at the endpoint.

Francisella tularensis reference qPCR assays

We compared results obtained with the Biotoxis qPCR detection ® kit with those obtained with three previously validated qPCR methods, which are routinely used at the French National Reference Center for Francisella (French NRCF) (Grenoble University Hospital, Grenoble, France). One qPCR test (referred to as ISFtu2-qPCR) targets the ISFtu2 insertion sequence present in multiple copies in the F. tularensis genome [START_REF] Versage | Development of a multitarget real-time TaqMan PCR assay for enhanced detection of Francisella tularensis in complex specimens[END_REF]. The second one (Tul4-qPCR) targets the gene encoding the single copy Tul4 surface protein-encoding gene [START_REF] Versage | Development of a multitarget real-time TaqMan PCR assay for enhanced detection of Francisella tularensis in complex specimens[END_REF]. The last one (Type B-qPCR) targets a DNA fragment located between ISFtu2 and a flanking 3´ region and is specific for F. tularensis subsp. holarctica [START_REF] Kugeler | Real-time PCR for Francisella tularensis types A and B[END_REF].

These three qPCR tests were performed using the same protocol. Each of the PCR mixtures (20 µl) contained 10 µl of 2X TaqMan™ Fast Advanced PCR Master Mix (Applied Biosystems, Thermo Fisher Scientific, Vilnius, Lithuania), 0.4 µl of each 10 µM primers, 0.4 µl of 2µM probe, 3.8 µl of water, and 5 µl of DNA sample (at variable concentration according to sample type, see below). The PCRs were run on a Lightcycler ® 480 instrument II (Roche) with an initial enzyme activation step of 50°C for 2 min and 95°C for 2 min, followed by 45 cycles of denaturation at 95°C for 3 sec, and annealing and extension at 60°C for 30 sec. The results were analyzed at the endpoint.

DNA extraction methods

For bacterial strains and clinical samples, DNA extraction was obtained using the QIAamp DNA Minikit (Qiagen, Courtaboeuf, France), according to the manufacturer's recommendations.

For artificial and environmental water samples, one liter of water was filtered through 0.22 µm or 0.45 µM filters, and DNA was extracted from the filter using the NucleoMag DNA/RNA Water ® kit (Macherey-Nagel, Düren, Germany), according to the manufacturer's recommendations.

Concentrations of bacterial strain DNA extracts and environmental water DNA extracts were then assessed using a NanoDrop 2000c spectrophotometer (Thermo Fisher Scientific).

Bacterial strains

We tested 90 Francisella sp. strains, including 86 clinical strains of F. tularensis subsp. holarctica, one clinical strain of F. philomiragia, and the reference strains F. philomiragia ATCC 25015, F. novicida CIP 56.12, and F. tularensis subsp. holarctica LVS NCTC 10857 (Table 1). Clinical strains of Francisella sp. were previously identified at the French NRCF.

F. philomiragia was identified by whole 16S rDNA sequencing [START_REF] Kreitmann | Disseminated Infection Caused by Francisella philomiragia, France, 2014[END_REF]. F. tularensis subsp.

holarctica was identified at the subspecies level by combining a positive ISFtu2-or Tul4-qPCR test, and either a positive Type B-qPCR or PCR-amplification and sequencing of the expected 16S-23S intergenic region [START_REF] Maurin | Human tularemia in France, 2006-2010[END_REF]. The French NRCF owns all the above strains, and specific authorizations have been obtained from the Agence Nationale de Sécurité du Médicament et des Produits de santé (ANSM, authorization number ADE-103892019-7).

Besides, 24 reference or clinical strains belonging to bacterial species other than Francisella sp. were used (Table 1).

Bacteria were grown on chocolate agar medium supplemented with PolyViteX ® (bioMérieux, Marcy-l'Etoile, France) or on sheep blood agar medium (bioMérieux, Marcy-l'Etoile, France), at 35°C in a 5% CO 2 -enriched atmosphere for one or two day(s). Francisella tularensis strains were grown in a biosafety level 3 laboratory. DNA extracts from Francisella sp. strains were prepared at 10 ng/µl concentration for analysis with the Biotoxis qPCR detection ® kit. DNA extracts from four clinical strains of F. tularensis subsp. holarctica, one clinical strain of F. philomiragia, F. philomiragia ATCC 25015, and F. novicida CIP 56.12 were used to compare Ct obtained with the Biotoxis qPCR to those of the ISFtu2-, Tul4-and Type B-qPCR tests (Table 2). For non-Francisella strains, three DNA extract concentrations were used (0.1, 1, and 10 ng/µl).

Clinical Specimens

For sensitivity purposes, we tested 31 clinical samples (mainly lymph node and respiratory samples) collected for routine medical care in 30 tularemia patients, including 29 confirmed cases and one probable case (Table 3). These samples were received at the French NRCF between 2018 and 2019 for diagnostic expertise. A tularemia confirmed case was defined as a clinically compatible disease with detection of F. tularensis from any clinical specimen by culture or PCR (ISFtu2-or Type B-qPCR, Ct ≤ 35), or seroconversion, or a fourfold (or greater) change in serum antibody titers to F. tularensis antigen between acute and convalescent-phase sera. A probable case was defined as a clinically-compatible disease with a single positive serum sample. According to our laboratory's routine procedure, all clinical samples were first tested using ISFtu2-qPCR for F. tularensis detection [START_REF] Versage | Development of a multitarget real-time TaqMan PCR assay for enhanced detection of Francisella tularensis in complex specimens[END_REF]. Positive samples were further tested using Type B-qPCR for the identification of subspecies F. tularensis subsp. holarctica [START_REF] Kugeler | Real-time PCR for Francisella tularensis types A and B[END_REF]. When possible, F. tularensis culture was also performed. These samples were analyzed by the Biotoxis qPCR detection ® kit retrospectively. DNA extracts were analyzed pure and diluted to 1/10 and 1/100. Samples were considered positive if at least one of the three DNA dilutions tested was positive. Negative results were duplicated for confirmation.

For specificity purposes, we also tested 30 clinical samples from patients for which the French NRCF excluded tularemia diagnosis because of negative diagnostic tests for F. tularensis, including eight samples positive for Bartonella henselae PCR test. All these samples were collected as part of routine patients' care and analyzed retrospectively using the Biotoxis qPCR detection ® kit.

Environmental samples

We first determined the limit of detection (LOD) of the Biotoxis qPCR using F. tularensisspiked water samples. For this purpose, a water sample collected in the environment was first sterilized by filtration on a 0.22 µm filter. Several aliquots were then inoculated with F. tularensis subsp. holarctica LVS NCTC 10857 strain at concentrations ranging from 0.1 to 10,000 CFU/l. One liter of each aliquot was filtered through a 0.22 µM filter, and DNA was extracted from the filter. The DNA extracts were tested using the Biotoxis qPCR detection ® kit (in triplicate) and ISFtu2-, Tul4-and Type B-qPCR taken as controls.

We then tested 57 surface water samples collected in France in 2019 from various aquatic environments. One liter of each sample was passed through a 0.45 or 0.22 µM filter, from which DNA was extracted. DNA extracts were then adjusted to 10 ng/µl and tested in duplicate by the ISFtu2-, Tul4-, and Type B-qPCR tests. These qPCR tests were considered positive only when both duplicate tests displayed a Ct ≤ 36 for ISFtu2-qPCR or a Ct < 40 for Tul4-and Type B-qPCRs. However, the presence of F. tularensis DNA was considered confirmed only for water samples with a positive Type B-qPCR test, which can specifically detect F. tularensis subsp. holarctica strains found in France. Water samples were then tested using the Biotoxis qPCR detection ® kit, and results were compared to those of the three previous qPCR tests.

RESULTS

Bacterial strains

The Biotoxis qPCR gave a strongly positive signal (Ct values between 15 to 22) for the 86 clinical strains of F. tularensis subsp. holarctica and for the reference strain F. tularensis subsp. holarctica LVS NCTC 10857, corresponding to a 100% sensitivity for the tested Type B tularemia strains. DNA extracts from four clinical strains of F. tularensis subsp. holarctica were tested to determine the analytical sensitivity of the Biotoxis qPCR, comparatively to those of the ISFtu2-, Tul4-and Type B-qPCR tests. The Ct ranges for these four samples were 18-20 for the Biotoxis qPCR, 12-14 for ISFtu2-qPCR, 15-19 for Tul4-qPCR, and 16-19 for Type B-qPCR (Table 2).

The Biotoxis qPCR also gave a strongly positive signal for F. novicida CIP 56.12 strain, like the ISFtu2 and Tul4-qPCR tests [START_REF] Versage | Development of a multitarget real-time TaqMan PCR assay for enhanced detection of Francisella tularensis in complex specimens[END_REF]. As expected, Type B-qPCR was negative for this strain (Table 2). Biotoxis qPCR did not amplify the two F. philomiragia strains tested. The ISFtu2-qPCR gave a week signal for this species, while Tul4 and Type B-qPCRs were negative (Table 2) [START_REF] Versage | Development of a multitarget real-time TaqMan PCR assay for enhanced detection of Francisella tularensis in complex specimens[END_REF].

The Biotoxis qPCR was negative for 21 non-Francisella strains but gave a weak signal (Ct between 34 and 37 at 10 ng/µL of DNA concentration) for Streptococcus salivarius, Pseudomonas aeruginosa CIP 5933, and Neisseria elongata strains. For these three strains, testing lower DNA concentrations (0.1 to 1 ng/µl) abolished the amplification signal. Overall, the Biotoxis qPCR displayed a 96.30% specificity for the 27 non-type B strains tested owing to the cross-amplification of F. novicida.

Clinical samples

The 31 clinical samples collected from 30 tularemia patients included 24 lymph nodes, four respiratory samples, two peritoneal samples, and one osteoarticular sample (Table 3).

Tests were positive for 31/31 clinical samples for ISFTu2-qPCR, 29/31 for Type B-qPCR, and 28/31 for Biotoxis qPCR (Table 3). Therefore, the Biotoxis qPCR test's sensitivity could be evaluated at 90.32% and 96.55% compared to ISFtu2-and Type B-qPCR tests, respectively. The Ct ranged from 20.47 to 36.61 for ISFtu2-qPCR (with 30/31 tests with a Ct ≤ 35), 28.89 to 39.71 (20/31 tests with a Ct ≤ 35) for Type B-qPCR, and 27.37 to 39.06 (15/31 tests with a Ct ≤ 35) for Biotoxis qPCR (Table 3).

The Biotoxis qPCR was positive for 27/31 pure DNA extracts (with Ct ranging from 27.37 to 39.06), 19/31 DNA extracts diluted to the 1/10 (Ct, 29.85-39.43), and 13/31 DNA extracts diluted to the 1/100 (Ct, 33.26-39.26). Interestingly, sample S4 was positive for ISFtu2-qPCR, Type B-qPCR, and Biotoxis qPCR only when diluted to the 1/100, suggesting the presence of PCR inhibitors.

The 30 clinical samples from patients for which tularemia diagnosis was excluded corresponded to 14 lymph nodes, six blood samples, five abscesses, one respiratory sample, and four biopsies. The Biotoxis qPCR gave negative results for these 30 clinical samples, including the eight patients with bartonellosis, corresponding to a 100% specificity.

Environmental samples

Water samples artificially inoculated with F. tularensis subsp. holarctica LVS NCTC 10857 from 0.1 CFU/l to 10,000 CFU/l were analyzed by Biotoxis qPCR and by ISFTu2-, Tul4-and Type B-qPCR. Biotoxis qPCR detected F. tularensis from 1,000 CFU/l (with a Ct at 34.47). It was less sensitive than Type B-qPCR (positive from 100 CFU/l with a Ct at 38.23), Tul4-qPCR (positive from 10 CFU/l with a Ct at 36.96), and ISFtu2-qPCR (positive from 0.1 CFU/l with a Ct at 37.57).

The 57 environmental water samples collected in France were previously tested using the ISFtu2-, Tul4-, and Type B-qPCR tests. Fifteen were positive for the ISFtu2-qPCR, nine were positive for both ISFtu2-qPCR and Tul4-qPCR, and four were positive for ISFtu2-qPCR, Tul4-qPCR, and Type B-qPCR. The Biotoxis qPCR was positive for six (40%) of the 15 samples positive for ISFtu2-qPCR, five of the nine samples positive for both ISFtu2-and Tul4-qPCRs, and four samples positive for ISFtu2-, Tul4-and Type B-qPCRs (Table 4). The Biotoxis qPCR test was negative for all 42 samples negative for the ISFTu 2-, Tul 4-and Type B-qPCR tests (Table 4).

DISCUSSION

In this study, we evaluated the commercial Biotoxis qPCR detection® kit's performances for the detection of F. tularensis in clinical and water samples, comparatively to previously validated qPCR tests recommended by the World Health Organization for tularemia diagnosis (11).

We first evaluated this kit's ability to detect clinical and reference strains of F. tularensis previously identified in our laboratory. The 86 clinical strains and the reference LVS strain of F. tularensis subsp. holarctica gave a strong amplification signal with the Biotoxis qPCR (Ct between 15 and 22 for a DNA extract standardized at 10ng/µl). Similar Ct values were obtained with the qPCR tests targeting the single-copy Tul4 or Type B-specific DNA sequences. In contrast, lower Cts were obtained with the multi-copy ISFtu2 target (26 to 30 copies in F. tularensis subsp. holarctica genome ( 7)) (Table 2). To evaluate the specificity of the Biotoxis qPCR, we tested two F. philomiragia strains, one F. novicida strain, and 24 strains not belonging to Francisella species. The Biotoxis qPCR gave a strongly positive signal for the reference strain of F. novicida. This result was not unexpected since F. novicida (also referred to as F. tularensis subsp. novicida) has ≥ 97.7% similarity at the genome level with F. tularensis [START_REF] Larsson | Molecular evolutionary consequences of niche restriction in Francisella tularensis, a facultative intracellular pathogen[END_REF]. The same cross-amplification has been described for the ISFtu2-and Tul4-qPCR tests [START_REF] Versage | Development of a multitarget real-time TaqMan PCR assay for enhanced detection of Francisella tularensis in complex specimens[END_REF]. Differentiating these two closely related microorganisms using a qPCR test remains highly challenging. However, such cross-amplification currently has little impact on tularemia diagnosis because human infections with F. novicida are rare and associated with clinical and epidemiological contexts different from those of tularemia (4). Additional diagnostic tests are usually performed for tularemia diagnostic confirmation and differentiation of type A and type B infections (11). Because F. novicida is an aquatic bacterium, the situation is different when testing environmental water samples. In this case, the Biotoxis qPCR test is not sufficiently discriminating. A more specific test must be performed for accurate differentiation between F. novicida and F. tularensis. Therefore, in the context of bioterrorism, the Biotoxis qPCR kit is currently not specific enough for rapid and accurate confirmation of the presence of F. tularensis in environmental samples.

The Biotoxis qPCR was negative for F. philomiragia, confirming the absence of crossamplification of this other aquatic bacterium. The Biotoxis qPCR was also negative for 21 non-Francisella species tested, representing common human pathogens. When testing high DNA concentrations (10 ng/µl), we observed a weak qPCR signal (Ct ≥ 34) for the S. We did not include F. tularensis subsp. tularensis (Type A) strains because we do not possess such strains in the French NRCF. The genes classically used to target F. tularensis (i.e., ISFtu2 element and the 23kDa, fopA, and tul4 genes) detect all four tularensis subspecies [START_REF] Versage | Development of a multitarget real-time TaqMan PCR assay for enhanced detection of Francisella tularensis in complex specimens[END_REF].

Although the Biotoxis qPCR detection® kit's targeted genes are confidential, the manufacturer validated during the development process that this test can detect both Type A and Type B strains. This kit's performance for Type A strains in different sample types will have to be checked by further studies.

As for clinical specimens, we tested 31 samples previously collected from 30 tularemia patients. At the time of diagnosis, all samples were positive for the ISFtu2-qPCR (Ct ranges of 20.47-36.61) and 29/31 for Type B-qPCR (Ct ranges of 28.89-39.71). The Biotoxis qPCR was positive for 28/31 clinical samples with Ct ranging from 27.37 to 39.06 (Table 3).

Therefore, the Biotoxis qPCR tests' sensitivity could be evaluated at 90.32% and 96.55% compared to ISFtu2-and Type B-qPCR tests, respectively. The F. tularensis subsp. holarctica genome contains 26 to 30 copies of the ISFtu2 (7), explaining the higher sensitivity of the ISFtu2-qPCR compared to the Tul4-and Type B-qPCR tests targeting a single DNA copy.

However, the ISFtu2 insertion sequence is also found in the genome of other Francisella species, including F. novicida and F. philomiragia [START_REF] Versage | Development of a multitarget real-time TaqMan PCR assay for enhanced detection of Francisella tularensis in complex specimens[END_REF]. The Biotoxis qPCR displayed similar sensitivity to the Type B-qPCR. Ct values higher than 35 were found for 9/29 samples for Type B-qPCR and 13/28 for Biotoxis qPCR. Such high Ct values likely reflected the low F. tularensis inoculum and the presence of PCR-inhibitors in the tested clinical samples. However, for the Biotoxis qPCR test, no Ct threshold is specified by the manufacturer.

Overall, this test's sensitivity could be considered very satisfying, taking into account its multiplex nature. Besides, clinical samples were stored at -80°C for 1-2 years before Biotoxis qPCR testing, which could have slightly altered DNA quality. Regarding specificity, no amplification was observed for the 30 F. tularensis-free clinical specimens with this kit.

When testing water samples artificially contaminated with F. tularensis subsp. holarctica, we found a LOD of 1,000 CFU/l for the Biotoxis qPCR, 100 CFU/l for Type B-qPCR, 10 CFU/l for Tul4-qPCR, and 0.1 CFU/l for ISFtu2-qPCR. Here again, the lower LOD of ISFTu2-qPCR could be explained by this target's multi-copy nature [START_REF] Versage | Development of a multitarget real-time TaqMan PCR assay for enhanced detection of Francisella tularensis in complex specimens[END_REF]. The higher LOD of the Biotoxis qPCR compared to those of the Tul4-and Type B-qPCR assays could be related to the multiplex nature of this commercial test. Multiplexed qPCR tests usually display lower analytical sensitivities than their simplex counterparts do [START_REF] Elnifro | Multiplex PCR: Optimization and Application in Diagnostic Virology[END_REF]. process. However, further studies will be needed to assess the sensitivity and specificity of the Biotoxis kit for detection of Y. pestis and B. anthracis. Consequently, our study does not enable us to claim the usefulness of the Biotoxis qPCR kit in the context of bioterrorism.

Apart the investigation of a suspected bioterrorist attack, we beleave this test could be useful for rapid exploration of the potential sources of human infections during natural tularemia outbreaks.

In conclusion, the Biotoxis qPCR detection ® kit displayed good performances for detecting F. tularensis in clinical specimens and environmental water samples. However, the cross-amplification of F. novicida should be taken into account. This kit was easy to use, and results were available within 60 min. It can be useful for the rapid detection of F. tularensis DNA in many clinical samples, especially in the context of a tularemia outbreak. It can also be used to detect F. tularensis in a large number of environmental samples. The Biotoxis qPCR detection ® kit has been primarilly designed for simultaneous detection of F. tularensis, B. anthracis, and Y. pestis in a bioterrorislm context. Futher studies are needed to assess the performances of this kit for detection of the two later pathogens.

Species (strain)

Species (strain)

  salivarius, P. aeruginosa, and N. elongata strains. Using lower DNA concentrations could eliminate such non-specific signals. When working on DNA extracts from bacterial strains, it should be recommended to work with DNA concentrations of 0.1 ng/µl to avoid unspecific amplification.

TABLE 2 . Biotoxis qPCR testing of bacterial strains

 2

	F. tularensis subsp. holarctica clinical strains	Enterococcus faecium (CIP 5432)
	(86 strains, including Ft5-46, Ft48-65, Ft67-74,
	Ft76-80, Ft83-89, Ft91, Ft92-96)
	F. tularensis subsp. holarctica	Bacillus subtilis (ATCC 6633)
	(LVS NCTC 10857)
	F. novicida (CIP 56.12)	Haemophilus influenzae (ATCC 49766)
	F. philomiragia (Ft47 clinical strain)	Acinetobacter baumanii (ATCC 19606)
	F. philomiragia (ATCC 25015)	Escherichia coli (ATCC 25922)
	Corynebacterium jeikeium (CIP 8251)	Enterobacter cloacae (ATCC 13047)
	Staphylococcus epidermidis (CIP 103627)	Klebsiella pneumoniae (ATCC 35657)
	Staphylococcus aureus (ATCC 6538)	Staphylococcus sciuri (ATCC 29061)
	Streptococcus agalactiae (ATCC 12400)	Stenotrophomonas maltophilia (ATCC 17666)
	Streptococcus pneumoniae (ATCC 49619)	Pseudomonas aeruginosa (CIP 5933)
	Streptococcus uberis (ATCC 9727)	Streptococcus pyogenes (CIP 104226)
	Streptococcus salivarius (clinical strain)	Neisseria elongata (clinical strain)
	Streptococcus mitis (CIP 103335)	Moraxella catharalis (clinical strain)
	Streptococcus oralis (clinical strain)	Serratia marcescens (CIP 103551)
	Enterococcus faecalis (ATCC 29212)

fourfold rise in antibody titers; *: samples from the same patient

ACKNOWLEDGMENTS

The authors declare that they have no conflict of interest. Bertin Bioreagent provided the Biotoxis qPCR detection® kit used in this study but was not involved in the study design, result interpretation, and this manuscript's content. Bertin Bioreagent thanks the interministerial program of R&D against CBRNE that financed the test development

We then tested 57 environmental water samples collected from natural aquatic environments.

The Biotoxis qPCR was positive for 6/15 samples positive for ISFtu2-qPCR, 5/9 Tul4-qPCR positive samples, and 4/4 Type B-qPCR positive samples (Table 4). As expected, the Biotoxis qPCR did not detect some positive samples for ISFtu2-and Tul4-qPCR tests. However, only samples positive for the highly specific Type B-qPCR test could be considered genuinely contaminated with F. tularensis (type B strain). The same samples tested positive with the Biotoxis qPCR test. This result likely indicates the higher specificity of these two tests to detect F. tularensis DNA in aquatic environments. It should be highlighted that high Ct values were found for most qPCR-positive water samples, reflecting low bacterial loads, as previously reported in other environmental studies [START_REF] Janse | Environmental Surveillance of Zoonotic Francisella tularensis in the Netherlands[END_REF]. A much higher bacterial load would be expected in a bioterrorist attack context. It would have been attractive to culture these environmental water samples to correlate PCR and culture results. However, we did not try to culture them since it would be tedious because of 1/ the fastidious nature of F. tularensis and 2/ the high quantity of contaminant bacteria in these samples.

The Biotoxis qPCR detection ® kit is designed to perform multiple tests in a 96 wells plate format. Unlike other commercial products such as the BioFire FilmArray ® Biothreat Panel, it is not suitable for unit samples analysis. Consequently, the Biotoxis qPCR detection ® kit appears more appropriate for testing many biological or environmental samples at a moderate cost. In our hands, this kit displayed equivalent specificity but a slightly lower sensitivity than F. tularensis reference qPCR assays. However, the purpose of the Biotoxis kit is to simultaneously detect the presence of F. tularensis, Y. pestis and B. anthracis in a bioterrorism context. It is a ready-to-use kit that can be handled in all the laboratories equipped with a qPCR apparatus, without need for specific expertise. We did not evaluate the Biotoxis qPCR detection® kit's performances for the detection of B. anthracis and Y. pestis.

The kit was validated for all three pathogens by the manufacturer during the its development