Genomic Investigation of Virulence Potential in Shiga Toxin Escherichia coli (STEC) Strains From a Semi-Hard Raw Milk Cheese

Shiga-toxin-producing Escherichia coli (STEC) represents a significant cause of foodborne disease. In the last years, an increasing number of STEC infections associated with the consumption of raw and pasteurized milk cheese have been reported, contributing to raise the public awareness. The aim of this study is to evaluate the main genomic features of STEC strains isolated from a semi-hard raw milk cheese, focusing on their pathogenic potential. The analysis of 75 cheese samples collected during the period between April 2019 and January 2020 led to the isolation of seven strains from four stx-positive enrichment. The genome investigation evidenced the persistence of two serotypes, O174:H2 and O116:H48. All strains carried at least one stx gene and were negative for eae gene. The virulence gene pattern was homogeneous among the serogroup/ST and included adherence factors (lpfA, iha, ompT, papC, saa, sab, hra, and hes), enterohemolysin (ehxA), serum resistance (iss, tra), cytotoxin-encoding genes like epeA and espP, and the Locus of Adhesion and Autoaggregation Pathogenicity Islands (LAA PAIs) typically found in Locus of Enterocyte Effacement (LEE)-negative STEC. Genome plasticity indicators, namely, prophagic sequences carrying stx genes and plasmid replicons, were detected, leading to the possibility to share virulence determinants with other strains. Overall, our work adds new knowledge on STEC monitoring in raw milk dairy products, underlining the fundamental role of whole genome sequencing (WGS) for typing these unknown isolates. Since, up to now, some details about STEC pathogenesis mechanism is lacking, the continuous monitoring in order to protect human health and increase knowledge about STEC genetic features becomes essential

The rapid spread of SARS-COV-2 Omicron variant in Italy reflected early through wastewater surveillance

The SARS-CoV-2 Omicron variant emerged in South Africa in November 2021, and has later been identified worldwide, raising serious concerns. A real-time RT-PCR assay was designed for the rapid screening of the Omicron variant, targeting characteristic mutations of the spike gene. The assay was used to test 737 sewage samples collected throughout Italy (19/21 Regions) between 11 November and 25 December 2021, with the aim of assessing the spread of the Omicron variant in the country. Positive samples were also tested with a real-time RT-PCR developed by the European Commission, Joint Research Centre (JRC), and through nested RT-PCR followed by Sanger sequencing. Overall, 115 samples tested positive for Omicron SARS-CoV-2 variant. The first occurrence was detected on 7 December, in Veneto, North Italy. Later on, the variant spread extremely fast in three weeks, with prevalence of positive wastewater samples rising from 1.0% (1/104 samples) in the week 5–11 December, to 17.5% (25/143 samples) in the week 12–18, to 65.9% (89/135 samples) in the week 19–25, in line with the increase in cases of infection with the Omicron variant observed during December in Italy. Similarly, the number of Regions/Autonomous Provinces in which the variant was detected increased from one in the first week, to 11 in the second, and to 17 in the last one. The presence of the Omicron variant was confirmed by the JRC real-time RT-PCR in 79.1% (91/115) of the positive samples, and by Sanger sequencing in 66% (64/97) of PCR amplicons. In conclusion, we designed an RT-qPCR assay capable to detect the Omicron variant, which can be successfully used for the purpose of wastewater-based epidemiology. We also described the history of the introduction and diffusion of the Omicron variant in the Italian population and territory, confirming the effectiveness of sewage monitoring as a powerful surveillance tool

Temporal trends in airborne pollen seasonality: evidence from the Italian POLLnet network data

Airborne pollen reflects local vegetative composition and is a proxy for flowering phase. Long-term pollen data might reflect changes in biodiversity and phenology, attributable also to the effect of climate change. The present study, based on pollen data collected within the Italian aerobiological network POLLnet, aimed to verify whether there is any evidence of temporal changes in pollen season timing and its relation with meteorological variables. To this purpose, nine stations located in North and Central Italy were selected, and twelve pollen taxa, both arboreal and herbaceous, were considered. For each taxon and station, 11–17-year datasets of airborne pollen concentration within the period 2000–2016 were analysed. Four different pollen season descriptors were elaborated (start, end and peak date, season length) and analysed their temporal trend, also in relation to temperature and precipitation. Overall, the results showed a negative temporal trend in pollen season starting date, which indicates a tendency towards an earlier flowering for Corylus, Quercus, Gramineae and Urticaceae in all stations (even if statistically significant in six out of 36 cases). The effect of meteorological parameters was evidenced by negative correlations between pollen season starting date and temperature. With the exception of Olea, Ambrosia and Artemisia, all the remaining pollen taxa showed significant (negative) correlations between pollen season start date and average temperature of the previous months in at least half of the stations. As for precipitation, no relevant correlations were detected with pollen season parameters. The results are also interpreted considering the different biogeographic areas in which the nine stations are located. Long-term pollen dataset is useful in phenological studies and for the detection of climate change effect

The Italian Network POLLnet: the database as background to detect airborne pollen trends and investigate climate change effects

Airborne pollen reflects structure and changes in vegetation .It is well known that pollen seasons and their intensity could help to detect the effects of climatic changes so pollen is a good bioindicator. Our investigation has been supported by a national network among regional agencies; each centre refers to the same protocol compliant with UNI 11108 subsequent amendments . Thus, it was possible to obtain reliable data, consistent with accuracy and precision requirements. Aim of this work is to draw attention on possible trends in the parameters describing the pollen season and pollen amount and to investigate the role of meteorological factors. Aerobiological data were validated; comprehensiveness requirements of the data set were established. Nine different pollen descriptors were considered and examined in relation with different meteorological parameters through a non parametric statistical approach. We took into account 9 stations in northern and central Italy, analysing 12 herbaceous and arboreal taxa during a time period from 2000 to 2017. The first results show a homogeneity of trends of the pollen season’s indicators. Trends of general advance in the starting date for Poaceae, Urticaceae, Quercus and Corylus and in the peak date for Poaceae and Corylus is one of the most relevant signals found. On the other hand, trends related to indicators of pollen production (peak value and pollen index), which are certainly more influenced by local features, are less homogeneous. The effects of climate change are underlined by several relevant signals of (negative) correlation with temperature. For some taxa it is possible to highlight a relevant connection both with minimum temperature (with particular reference to the winter and autumn one) and with the maximum (winter and spring) temperature; as regards precipitations, relevant values of correlation appear only occasionally. Conclusions: The obtained results are reported and discussed in light of the state of the art

The method of the Italian network POLLnet for counting and evaluating the concentration of airborne particles in a daily sample

Airborne pollen monitoring is of concern for health purposes as well as for studies on climate changes and biodiversity. The reliability of data estimates depends on the accuracy and precision of pollen counts (Gottardini et al., 2008). An important aspect of the microscope analysis, heavily influencing this reliability, is the choice of the minimal surface to be read on a microscope slide. At the moment, operators seem to argue among 10%, 15% and 20% of the target surface. The Italian network POLLnet searched a criterion both on experimental and statistics basis. For this purpose, three microscope slides, with low, medium and high amounts of particles, were read by twenty experienced aerobiologists. Each slide was analyzed on 100% of target surface, as well as 10%, 15% and 20%. The statistic approach applied the Poisson distribution to search the minimal surface to examine in order to find at least 1 pollen grain if on the total target sample there are 5 grains, or 0.5 particles/m3 that is the threshold concentration for the detection of most of the monitored families. This study confirmed that the variability of data decreases as the examined area increases. In particular, when 10% of the target area is examined, up to 45% of the pollen species can escape the analysis; when the slides were examined on the wider areas (15% and 20%), this lost of taxa decreased up to 15%. Also, the repeatability and the reproducibility of the analysis varied significantly on the basis of the percentages of the target area examined. Moreover, the statistic approach indicated that 14% is the minimal area to examine to find at least 1 airborne particle on a total of 5, with a confidence of 50%. Even if the experimental data suggest that the ideal surface would be at least 20%, both the experimental and the statistical approach indicate that adopting as a minimum reading limit 15% of the sampling surface is still acceptable

The rapid spread of SARS-COV-2 Omicron variant in Italy reflected early through wastewater surveillance

The SARS-CoV-2 Omicron variant emerged in South Africa in November 2021, and has later been identified worldwide, raising serious concerns. A real-time RT-PCR assay was designed for the rapid screening of the Omicron variant, targeting characteristic mutations of the spike gene. The assay was used to test 737 sewage samples collected throughout Italy (19/21 Regions) between 11 November and 25 December 2021, with the aim of assessing the spread of the Omicron variant in the country. Positive samples were also tested with a real-time RT-PCR developed by the European Commission, Joint Research Centre (JRC), and through nested RT-PCR followed by Sanger sequencing. Overall, 115 samples tested positive for Omicron SARS-CoV-2 variant. The first occurrence was detected on 7 December, in Veneto, North Italy. Later on, the variant spread extremely fast in three weeks, with prevalence of positive wastewater samples rising from 1.0% (1/104 samples) in the week 5–11 December, to 17.5% (25/143 samples) in the week 12–18, to 65.9% (89/135 samples) in the week 19–25, in line with the increase in cases of infection with the Omicron variant observed during December in Italy. Similarly, the number of Regions/Autonomous Provinces in which the variant was detected increased from one in the first week, to 11 in the second, and to 17 in the last one. The presence of the Omicron variant was confirmed by the JRC real-time RT-PCR in 79.1% (91/115) of the positive samples, and by Sanger sequencing in 66% (64/97) of PCR amplicons. In conclusion, we designed an RT-qPCR assay capable to detect the Omicron variant, which can be successfully used for the purpose of wastewater-based epidemiology. We also described the history of the introduction and diffusion of the Omicron variant in the Italian population and territory, confirming the effectiveness of sewage monitoring as a powerful surveillance tool