Arbovirus screening of mosquitoes collected in 2022 in Emilia-Romagna, Italy, with the implementation of a real-time PCR for the detection of Tahyna virus.

Several Arboviruses (Arthropod-borne virus) are a concrete health risk. While some arboviruses, such as the West Nile virus (WNV) and the Usutu virus (USUV) are actively surveyed, others are neglected, including the Tahyna virus (TAHV). In this work, we tested - searching for all the three viruses - 37,995 mosquitoes collected in 95 attractive traps, baited by carbon dioxide, distributed in the lowlands of Emilia-Romagna, northern Italy, between 19 July and 12 August 2022. Among the 668 pools obtained, WNV was detected in 45 pools of Culex (Cx.) pipiens and USUV was recorded in 24 pools of the same mosquito; ten of these Cx. pipiens pools tested positive for both WNV and USUV. Interestingly, we recorded a significant circulation of both WNV lineage 1 (WNV-L1) and lineage 2 (WNV-L2): WNV-L1 strains were detected in 40 pools, WNV-L2 strains in three pools and both lineages were detected in two pools. TAHV was detected in 8 different species of mosquitoes in a total of 37 pools: Aedes (Ae.) caspius (25), Ae. albopictus (5), Ae. vexans (3), Cx. pipiens (2), Ae. cinereus (1) and Anopheles maculipennis sl (1). The significant number of Ae. caspius-pools tested positive and the estimated viral load suggest that this mosquito is the principal vector in the surveyed area. The potential involvement of other mosquito species in the TAHV cycle could usefully be the subject of further experimental investigation. The results obtained demonstrate that, with adequate sampling effort, entomological surveillance is able to detect arboviruses circulating in a given area. Further efforts must be made to better characterise the TAHV cycle in the surveyed area and to define health risk linked to this virus.

Spatiotemporal Distribution of Salmonella enterica in European Hedgehogs in Northern Italy.

Growing attention is being given to the European hedgehog (Erinaceus europaeus) because of its synanthropic behaviour and its potential role in harbouring parasites, viruses, fungi and bacteria and disseminating them to several animals and humans. Salmonella are the most frequently detected zoonotic bacteria that hedgehogs could transmit through contaminating water and food sources with faeces. This study aimed to determine the prevalence and distribution of Salmonella spp. in wild hedgehogs in the Emilia-Romagna region (northern Italy). From 2019 to 2022, 212 European hedgehogs that died naturally were tested for Salmonella spp. through culture isolation. Positive samples were subjected to serological typing. A total of 82 samples tested positive for Salmonella spp., with the overall Bayesian posterior estimated prevalence ranging from 35% (95% CI: 23-47%) to a maximum of 45% (95% CI: 31-59%) during the years considered and with an overall prevalence calculated at 39% (95% CI: 33-45%). Salmonella enterica Enteritidis and Veneziana were the most prevalent detected serovars in 65% and 17% of the positive samples, respectively. Since 2021, S. Typhimurium, S. Typhimurium Monofasica, S. Zaiman, S. Hessarek, S. Muenster, S. Isangi serovars, S. enterica subsp. Diarizonae and S. enterica subsp. Houtenae have been detected. These findings show a high prevalence of Salmonella spp. in tested hedgehogs, suggesting an important role of this animal species in the epidemiology of potentially zoonotic serovars circulating in the Emilia-Romagna region.

Unsupervised machine learning and geometric morphometrics as tools for the identification of inter and intraspecific variations in the Anopheles Maculipennis complex.

Geometric morphometric analysis was combined with two different unsupervised machine learning algorithms, UMAP and HDBSCAN, to visualize morphological differences in wing shape among and within four Anopheles sibling species (An. atroparvus, An. melanoon, An. maculipennis s.s. and An. daciae sp. inq.) of the Maculipennis complex in Northern Italy. Specifically, we evaluated: (1) wing shape variation among and within species; (2) the consistencies between groups of An. maculipennis s.s. and An. daciae sp. inq. identified based on COI sequences and wing shape variability; and (3) the spatial and temporal distribution of different morphotypes. UMAP detected at least 13 main patterns of variation in wing shape among the four analyzed species and mapped intraspecific morphological variations. The relationship between the most abundant COI haplotypes of An. daciae sp. inq. and shape ordination/variation was not significant. However, morphological variation within haplotypes was reported. HDBSCAN also recognized different clusters of morphotypes within An. daciae sp. inq. (12) and An. maculipennis s.s. (4). All morphotypes shared a similar pattern of variation in the subcostal vein, in the anal vein and in the radio-medial cross-vein of the wing. On the contrary, the marginal part of the wings remained unchanged in all clusters of both species. Any spatial-temporal significant difference was observed in the frequency of the identified morphotypes.  Our study demonstrated that machine learning algorithms are a useful tool combined with geometric morphometrics and suggest to deepen the analysis of inter and intra specific shape variability to evaluate evolutionary constrains related to wing functionality.

New Trends in the Occurrence of Yessotoxins in the Northwestern Adriatic Sea.

Yessotoxins (YTXs) are polycyclic toxic ether compounds produced by phytoplanktonic dinoflagellates which accumulate in filter-feeding organisms. We know that the water temperature in our areas Northwestern Adriatic Sea is optimal for the growth of potentially toxic algae (around 20 °C). In recent years, these temperatures have remained at these levels for longer and longer periods, probably due to global warming, which has led to an excessive increase in toxin levels. The interruption of mussel harvesting caused by algae negatively affects farmers' revenues and the availability of local fish, causing a major economic loss in Italy's main shellfish sector. METHODS: In the nine years considered, 3359 samples were examined: 1715 marine waters, 73 common clams; 732 mussels; 66 oysters; and 773 veracious clams. Bivalve molluscs were examined for the presence of marine biotoxins, including YTXs, while potentially toxic algae, including those producing YTXs, were searched for and counted in marine waters. The method adopted for the quantification of lipophilic toxins involves the use of an LC-MS/MS system. The enumeration of phytoplankton cells was performed according to the Utermhöl method. RESULTS: Between 2012 and 2020, 706 molluscs were tested for YTXs. In total, 246 samples tested positive, i.e., 34.84%. Of the positive samples, 30 exceeded the legal limit. CONCLUSION: In this regard, it is essential to develop and activate, as soon as possible, an "early warning" system that allows a better control of the production areas of live bivalve molluscs, thus allowing an optimal management of the plants in these critical situations.

Geometric morphometrics and machine learning as tools for the identification of sibling mosquito species of the Maculipennis complex (Anopheles).

Geometric morphometrics allows researchers to use the specific software to quantify and to visualize morphological differences between taxa from insect wings. Our objective was to assess wing geometry to distinguish four Anopheles sibling species of the Maculipennis complex, An. maculipennis s. s., An. daciae sp. inq., An. atroparvus and An. melanoon, found in Northern Italy. We combined the geometric morphometric approach with different machine learning alghorithms: support vector machine (SVM), random forest (RF), artificial neural network (ANN) and an ensemble model (EN). Centroid size was smaller in An. atroparvus than in An. maculipennis s. s. and An. daciae sp. inq. Principal component analysis (PCA) explained only 33% of the total variance and appeared not very useful to discriminate among species, and in particular between An. maculipennis s. s. and An. daciae sp. inq. The performance of four different machine learning alghorithms using procrustes coordinates of wing shape as predictors was evaluated. All models showed ROC-AUC and PRC-AUC values that were higher than the random classifier but the SVM algorithm maximized the most metrics on the test set. The SVM algorithm with radial basis function allowed the correct classification of 83% of An. maculipennis s. s. and 79% of An. daciae sp. inq. ROC-AUC analysis showed that three landmarks, 11, 16 and 15, were the most important procrustes coordinates in mean wing shape comparison between An. maculipennis s. s. and An. daciae sp. inq. The pattern in the three-dimensional space of the most important procrustes coordinates showed a clearer differentiation between the two species than the PCA. Our study demonstrated that machine learning algorithms could be a useful tool combined with the wing geometric morphometric approach.

Co-Circulation of Phleboviruses and Leishmania Parasites in Sand Flies from a Single Site in Italy Monitored between 2017 and 2020.

Sand flies transmit Leishmania infantum, which is responsible for causing leishmaniasis, as well as many phleboviruses, including the human pathogenic Toscana virus. We screened sand flies collected from a single site between 2017 and 2020 for the presence of both phleboviruses and Leishmania. The sand flies were sampled with attractive carbon dioxide traps and CDC light traps between May and October. We collected more than 50,000 sand flies; 2826 were identified at the species level as Phlebotomus perfiliewi (98%) or Phlebotomus perniciosus (2%). A total of 16,789 sand flies were tested in 355 pools, and phleboviruses were found in 61 pools (6 Toscana virus positive pools, 2 Corfou virus positive pools, 42 Fermo virus positive pools, and 7 Ponticelli virus positive pools, and 4 unidentified phlebovirus positive pools). Leishmania was found in 75 pools and both microorganisms were detected in 16 pools. We isolated nine phleboviruses from another 2960 sand flies (five Ponticelli viruses and for Fermo viruses), not tested for Leishmania; the complete genome of a Fermo virus isolate was sequenced. The simultaneous detection in space and time of the Fermo virus and L. infantum is evidence that supports the co-circulation of both microorganisms in the same location and partial overlap of their cycles. A detailed characterization of the epidemiology of these microorganisms will support measures to limit their transmission.

Mosquitoes of the Maculipennis complex in Northern Italy.

The correct identification of mosquito vectors is often hampered by the presence of morphologically indiscernible sibling species. The Maculipennis complex is one of these groups that include both malaria vectors of primary importance and species of low/negligible epidemiological relevance, of which distribution data in Italy are outdated. Our study was aimed at providing an updated distribution of Maculipennis complex in Northern Italy through the sampling and morphological/molecular identification of specimens from five regions. The most abundant species was Anopheles messeae (2032), followed by Anopheles maculipennis s.s. (418), Anopheles atroparvus (28) and Anopheles melanoon (13). Taking advantage of ITS2 barcoding, we were able to finely characterize tested mosquitoes, classifying all the Anopheles messeae specimens as Anopheles daciae, a taxon with debated rank to which we referred as species inquirenda (sp. inq.). The distribution of species was characterized by Ecological Niche Models (ENMs), fed by recorded points of presence. ENMs provided clues on the ecological preferences of the detected species, with An. daciae sp. inq. linked to stable breeding sites and An. maculipennis s.s. more associated to ephemeral breeding sites. We demonstrate that historical Anopheles malaria vectors are still present in Northern Italy.