Antibodies Against Hepatitis E Virus (HEV) in European Moose and White-Tailed Deer in Finland

The main animal reservoirs of zoonotic hepatitis E virus (HEV) are domestic pigs and wild boars, but HEV also infects cervids. In this study, we estimated the prevalence of HEV in Finnish cervid species that are commonly hunted for human consumption. We investigated sera from 342 European moose (Alces alces), 70 white-tailed deer (Odocoileus virginianus), and 12 European roe deer (Capreolus capreolus). The samples had been collected from legally hunted animals from different districts of Finland during 2008–2009. We analysed the samples for total anti-HEV antibodies using a double-sandwich ELISA assay. Seropositive sera were analysed with RT-qPCR for HEV RNA. HEV seroprevalence was 9.1% (31/342) in moose and 1.4% (1/70) in white-tailed deer. None of the European roe deer were HEV seropositive (0/12). No HEV RNA was detected from samples of seropositive animals. HEV seropositive moose were detected in all districts. Statistically, HEV seroprevalence in moose was significantly higher (p Peer reviewe

Contamination by Norovirus and Adenovirus on Environmental Surfaces and in Hands of Conscripts in Two Finnish Garrisons

This study investigated the presence of norovirus and adenovirus, especially enteric adenovirus, on the environmental surfaces (n = 481) and military conscripts' hands (n = 109) in two Finnish garrisons (A and B) in 2013 and 2014. A questionnaire study was conducted to reveal possible correlations between viral findings on the conscripts' hands and their acute gastroenteritis symptoms. In addition to the swab samples, 14 fecal samples were obtained for viral analysis. In total, norovirus was present in 9.0 % of the surface swabs in 2013, whereas enteric adenovirus was present in 0.0 % and non-enteric adenovirus in 9.4 %. In the same year, 2.6 % of the hand swabs contained norovirus, 2.6 % enteric adenovirus, and 40.3 % non-enteric adenovirus. Norovirus GI.6 was continually detected on the surfaces of garrison A, and identical virus was detected in some of the fecal samples. In garrison B, two slightly different norovirus GII.4 strains were present on the surfaces. The questionnaires revealed no recent acute gastroenteritis cases in garrison A, but in garrison B, where the norovirus-positive hand swabs were collected, 30.6 % of the conscripts reported of recent symptoms. In 2014, norovirus was rarely detected, but adenovirus was again frequently present, both on the surfaces and hands. Taken together, our results suggest that gastroenteritis outbreaks occurred in 2013, but not in 2014. Due to the low number of hand swabs positive for enteric viruses, no conclusions about associations between viral findings and gastroenteritis symptoms could be drawn. This study increased our understanding of the possible transmission of viruses via contaminated environment and hands.Peer reviewe

Improving the identification of the source of faecal pollution in water using a modelling approach : From multi-source to aged and diluted samples

The last decades have seen the development of several source tracking (ST) markers to determine the source of pollution in water, but none of them show 100% specificity and sensitivity. Thus, a combination of several markers might provide a more accurate classification. In this study Ichnaea® software was improved to generate predictive models, taking into account ST marker decay rates and dilution factors to reflect the complexity of ecosystems. A total of 106 samples from 4 sources were collected in 5 European regions and 30 faecal indicators and ST markers were evaluated, including E. coli, enterococci, clostridia, bifidobacteria, somatic coliphages, host-specific bacteria, human viruses, host mitochondrial DNA, host-specific bacteriophages and artificial sweeteners. Models based on linear discriminant analysis (LDA) able to distinguish between human and non-human faecal pollution and identify faecal pollution of several origins were developed and tested with 36 additional laboratory-made samples. Almost all the ST markers showed the potential to correctly target their host in the 5 areas, although some were equivalent and redundant. The LDA-based models developed with fresh faecal samples were able to differentiate between human and non-human pollution with 98.1% accuracy in leave-one-out cross-validation (LOOCV) when using 2 molecular human ST markers (HF183 and HMBif), whereas 3 variables resulted in 100% correct classification. With 5 variables the model correctly classified all the fresh faecal samples from 4 different sources. Ichnaea® is a machine-learning software developed to improve the classification of the faecal pollution source in water, including in complex samples. In this project the models were developed using samples from a broad geographical area, but they can be tailored to determine the source of faecal pollution for any user.The last decades have seen the development of several source tracking (ST) markers to determine the source of pollution in water, but none of them show 100% specificity and sensitivity. Thus, a combination of several markers might provide a more accurate classification. In this study Ichnaea (R) software was improved to generate predictive models, taking into account ST marker decay rates and dilution factors to reflect the complexity of ecosystems. A total of 106 samples from 4 sources were collected in 5 European regions and 30 faecal indicators and ST markers were evaluated, including E. coli, enterococci, clostridia, bifidobacteria, somatic coliphages, host-specific bacteria, human viruses, host mitochondrial DNA, host-specific bacteriophages and artificial sweeteners. Models based on linear discriminant analysis (LDA) able to distinguish between human and non-human faecal pollution and identify faecal pollution of several origins were developed and tested with 36 additional laboratory-made samples. Almost all the ST markers showed the potential to correctly target their host in the 5 areas, although some were equivalent and redundant. The LDA-based models developed with fresh faecal samples were able to differentiate between human and non-human pollution with 98.1% accuracy in leave-one-out cross-validation (LOOCV) when using 2 molecular human ST markers (HF183 and HMBif), whereas 3 variables resulted in 100% correct classification. With 5 variables the model correctly classified all the fresh faecal samples from 4 different sources. Ichnaea (R) is a machine-learning software developed to improve the classification of the faecal pollution source in water, including in complex samples. In this project the models were developed using samples from a broad geographical area, but they can be tailored to determine the source of faecal pollution for any user. (C) 2019 Elsevier Ltd. All rights reserved.Peer reviewe

Performance of bacterial and mitochondrial qPCR source tracking methods : A European multi-center study

With the advent of molecular biology diagnostics, different quantitative PCR assays have been developed for use in Source Tracking (ST), with none of them showing 100% specificity and sensitivity. Most studies have been conducted at a regional level and mainly in fecal slurry rather than in animal wastewater. The use of a single molecular assay has most often proven to fall short in discriminating with precision the sources of fecal contamination. This work is a multicenter European ST study to compare bacterial and mitochondrial molecular assays and was set to evaluate the efficiency of nine previously described qPCR assays targeting human-, cow/ ruminant-, pig-, and poultry-associated fecal contamination. The study was conducted in five European countries with seven fecal indicators and nine ST assays being evaluated in a total of 77 samples. Animal fecal slurry samples and human and non-human wastewater samples were analyzed. Fecal indicators measured by culture and qPCR were generally ubiquitous in the samples. The ST qPCR markers performed at high levels in terms of quantitative sensitivity and specificity demonstrating large geographical application. Sensitivity varied between 73% (PLBif) and 100% for the majority of the tested markers. On the other hand, specificity ranged from 53% (CWMit) and 97% (BacR). Animal-associated ST qPCR markers were generally detected in concentrations greater than those found for the respective human-associated qPCR markers, with mean concentration for the Bacteroides qPCR markers varying between 8.74 and 7.22 log10 GC/10 mL for the pig and human markers, respectively. Bacteroides spp. and mitochondrial DNA qPCR markers generally presented higher Spearman's rank coefficient in the pooled fecal samples tested, particularly the human fecal markers with a coefficient of 0.79. The evaluation of the performance of Bacteroides spp., mitochondrial DNA and Bifidobacterium spp. ST qPCR markers support advanced pollution monitoring of impaired aquatic environments, aiming to elaborate strategies for targetoriented water quality management.Peer reviewe