EPI-Net One Health reporting guideline for antimicrobial consumption and resistance surveillance data: a Delphi approach

Strategic and standardised approaches to analysis and reporting of surveillance data are essential to inform antimicrobial resistance (AMR) mitigation measures, including antibiotic policies. Targeted guidance on linking full-scale AMR and antimicrobial consumption (AMC)/antimicrobial residues (AR) surveillance data from the human, animal, and environmental sectors is currently needed. This paper describes the initiative whereby a multidisciplinary panel of experts (56 from 20 countries-52 high income, 4 upper middle or lower income), representing all three sectors, elaborated proposals for structuring and reporting full-scale AMR and AMC/AR surveillance data across the three sectors. An evidence-supported, modified Delphi approach was adopted to reach consensus among the experts for dissemination frequency, language, and overall structure of reporting; core elements and metrics for AMC/AR data; core elements and metrics for AMR data. The recommendations can support multisectoral national and regional plans on antimicrobials policy to reduce resistance rates applying a One Health approach.

One Health Consensus Report Annotation Checklist (OH-CRAC): A cross-sector checklist to support harmonized annotation of surveillance data in reports

To facilitate cross-sector integration of surveillance data it is necessary to improve and harmonize the meta-information provided in surveillance data reports. Cross-sector integration of surveillance results in sector-specific reports is frequently difficult as reports with a focus on a single sector often lack aspects of the relevant meta-information necessary to clarify the surveillance context. Such reporting deficiencies reduce the value of surveillance reports to the One Health community. The One Health Consensus Report Annotation Checklist (OH-CRAC), described in this paper along with potential application scenarios, was developed to improve the current practice of annotating data presented in surveillance data reports. It aims to provide guidance to researchers and reporting officers on what meta-information should be collected and provided to improve the completeness and transparency of surveillance data reports. The OH-CRAC can be adopted by all One Health-related sectors and due to its cross-sector design, it supports the mutual mapping of surveillance meta-information from sector-specific surveillance reports on federal, national and international levels. To facilitate the checklist completion, OH-CRAC is also available as an online resource that allows the collection of surveillance meta-information in an easy and user-friendly manner. Completed OH-CRAC checklists can be attached as annexes to the corresponding surveillance data reports or even to individual data files regardless of the data source. In this way, reports and data become better interpretable, usable and comparable to information from other sectors, improving their value for all surveillance actors and providing a better foundation for advice to risk managers.

A one health glossary to support communication and information exchange between the human health, animal health and food safety sectors

Collaboration across sectors, disciplines and countries is a key concept to achieve the overarching One Health (OH) objective for better human, animal and environmental health. Differences in terminology and interpretation of terms are still a significant hurdle for cross-sectoral information exchange and collaboration within the area of OH including One Health Surveillance (OHS). The development of the here described glossary is a collaborative effort of three projects funded within the One Health European Joint Programme (OHEJP). We describe the infrastructure of the OHEJP Glossary, as well as the methodology to create such a cross-sectoral web resource in a collaborative manner. The new OHEJP Glossary allows OH actors to identify terms with different or shared interpretation across sectors. Being aware of such differences in terminology will help overcome communication hurdles in the future and consequently support collaboration and a more inclusive development of OHS. The OHEJP Glossary was implemented as a web-based, user-friendly and searchable infrastructure that complies with the Findable, Accessible, Interoperable, Reusable (FAIR) data principles. Maintenance, enrichment and quality control of the OHEJP Glossary is supported through a flexible and updatable curation infrastructure. This increases the uptake potential and exploitation of the OHEJP Glossary by other OH initiatives or tools and services.

The Glossaryfication Web Service: an automated glossary creation tool to support the One Health community

In many interdisciplinary research domains, the creation of a shared understanding of relevant terms is considered the foundation for efficient cross-sector communication and interpretation of data and information. This is also true for the domain of One Health (OH) where many One Health Surveillance (OHS) documents rarely contain glossaries with a list of terms for which their specific meaning in the context of the given document is defined (Cornelia et al. 2018, Buschhardt et al. 2021). The absence of glossaries within these documents may lead to misinterpretation of surveillance results due to the wrong interpretation of terminology specifically when term definitions differ across OH sectors. Under the One Health EJP project ORION, the OHEJP Glossary was recently created. The OHEJP Glossary is a tool to improve communication and collaboration amongst OH sectors by providing an easy-to-use online resource that lists relevant OH terms and sector-specific definitions. To improve the accessibility of content from the OHEJP Glossary and support the creation of integrative glossaries in future OHS-related documents, the OHEJP Glossaryfication Web Service was created. This service can support the practical use of the OHEJP Glossary and other relevant online glossaries by OH professionals.

The Glossaryfication Web Service (GWS) is an application that automatically identifies terms in any uploaded text-based document and creates a document-specific list of matching definitions in selected online glossaries. This auto-generated document-specific glossary can easily be adjusted by the user, for example, by selecting the desired definition in case multiple definitions were found for a specific term. The document-specific glossary could then be downloaded, manually adjusted and finally included into the original document where it supports the correct interpretation of terminology used. Especially in sector-specific reports, such as from animal health or public health authorities, this can be beneficial to ensure the correct interpretation by other OH sectors in the future. The GWS was developed with the open-source desktop software KNIME Analytics Platform and runs as a web service on a KNIME Web Server infrastructure. The core data processing functionality in the GWS is based on KNIME’s Text Processing extension. KNIME's JavaScript nodes provided the basis for an interactive user interface where users can easily upload their files and select between different reference glossaries, such as the OHEJP Glossary, the CDC Glossary, the WHO Glossary or the EFSA Glossary. After retrieval of the user input settings, the GWS tags words within the provided document and maps these tagged words with matching entries in the selected glossaries. As the main output, the user receives a downloadable list of matching terms with their corresponding definitions, sectorial assignments and references, which can then be added by the user to the original document. The GWS is freely accessible via this link as well as the underlying KNIME workflow.

Stability of hepatitis E virus at high hydrostatic pressure processing

Hepatitis E virus (HEV) is the causative agent of acute and chronic hepatitis in humans. The zoonotic HEV genotype 3 is the main genotype in Europe. The foodborne transmission via consumption of meat and meat products prepared from infected pigs or wild boars is considered the major transmission route of this genotype. High hydrostatic pressure processing (HPP) is a technique, which can be used for inactivation of pathogens in food. Here, preparations of a cell culture-adapted HEV genotype 3 strain in phosphate-buffered saline (PBS) were subjected to HPP and the remaining infectivity was titrated in cell culture by counting fluorescent foci of replicating virus. A gradual decrease in infectivity was found by application of 100 to 600 MPa for 2 min. At 20 °C, infectivity reduction of 0.5 log₁₀ at 200 MPa and 1 log₁₀ at 400 MPa were observed. Slightly higher infectivity reduction of 1 log₁₀ at 200 MPa and 2 log₁₀ at 400 MPa were found by application of the pressure at 4 °C. At both temperatures, the virus was nearly completely inactivated (>3.5 log₁₀ infectivity decrease) at 600 MPa; however, low amounts of remaining infectious virus were observed in one of three replicates in both cases. Transmission electron microscopy showed disassembled and distorted particles in the preparations treated with 600 MPa. Time-course experiments at 400 MPa showed a continuous decline of infectivity from 30 s to 10 min, leading to a 2 log₁₀ infectivity decrease at 20 °C and to a 2.5 log₁₀ infectivity decrease at 4 °C for a 10 min pressure application each. Predictive models for inactivation of HEV by HPP were generated on the basis of the generated data. The results show that HPP treatment can reduce HEV infectivity, which is mainly dependent on pressure height and duration of the HPP treatment. Compared to other viruses, HEV appears to be relatively stable against HPP and high pressure/long time combinations have to be applied for significant reduction of infectivity.

Survival of Trichinella spiralis in cured meat products

Processing of meat is one possible approach to control meat-borne parasites. Processing methods such as freezing, cooking and irradiation are recommended for the control of Trichinella in pork, horse or game meat if specific technical conditions are fulfilled. Curing is a widely used preservation process influencing product characteristics such as shelf life, food safety, and taste. As curing methods are characterized by high parameter variability and predictions about inactivation of parasitic stages in raw meat products are difficult, curing and smoking are not recommended for Trichinella control. The objective of this study was to investigate the survival of T. spiralis in cured raw sausages taking into account water activity (aw-value), pH value, temperature, and time. For this purpose, four different types of sausage (Knackwurst, vacuum packed Knackwurst, short ripened salami, long ripened salami) were produced using T. spiralis infested batter. After production, the sausages were stored at product specific conditions for up to 35 days. During storage, pH value and aw-value of the sausages were monitored over time. Further, sausages of each type were digested using the magnetic stirrer method and the viability of the isolated larvae was assessed using a previously published larval motility test as a proxy for viability and infectivity of Trichinella larvae. In this context, we also introduce a three-level rated infectivity score (RIS) with a clear categorization scheme allowing the assessment of the infectivity of larvae. Based on the RIS, larvae isolated from the salamis were regarded as potentially infective until day 2 (short ripened salami) or day 3 (long ripened salami) post ripening, whereas in Knackwurst, potentially infective larvae were still found by day 8 post ripening. In contrast potentially infective larvae were detected in vacuum-packed Knackwurst until day 24 post ripening. Finally, using the RIS approach, data from previously published studies were collected and subjected to a correlation analysis to identify matrix factors linked to short Trichinella inactivation times.

STEM: An Open Source Tool for Disease Modeling

The Spatiotemporal Epidemiologic Modeler (STEM) is an open source software project supported by the Eclipse Foundation and used by a global community of researchers and public health officials working to track and, when possible, control outbreaks of infectious disease in human and animal populations. STEM is not a model or a tool designed for a specific disease; it is a flexible, modular framework supporting exchange and integration of community models, reusable plug-in components, and denominator data, available to researchers worldwide at www.eclipse.org/stem. A review of multiple projects illustrates its capabilities. STEM has been used to study variations in transmission of seasonal influenza in Israel by strains; evaluate social distancing measures taken to curb the H1N1 epidemic in Mexico City; study measles outbreaks in part of London and inform local policy on immunization; and gain insights into H7N9 avian influenza transmission in China. A multistrain dengue fever model explored the roles of the mosquito vector, cross-strain immunity, and antibody response in the frequency of dengue outbreaks. STEM has also been used to study the impact of variations in climate on malaria incidence. During the Ebola epidemic, a weekly conference call supported the global modeling community; subsequent work modeled the impact of behavioral change and tested disease reintroduction via animal reservoirs. Work in Germany tracked salmonella in pork from farm to fork; and a recent doctoral dissertation used the air travel feature to compare the potential threats posed by weaponizing infectious diseases. Current projects include work in Great Britain to evaluate control strategies for parasitic disease in sheep, and in Germany and Hungary, to validate the model and inform policy decisions for African swine fever. STEM Version 4.0.0, released in early 2019, includes tools used in these projects and updates technical aspects of the framework to ease its use and re-use.

The Spatiotemporal Epidemiologic Modeler (STEM) is an open source software project supported by the Eclipse Foundation and used by a global community of researchers and public health officials working to track and, when possible, control outbreaks of infectious disease in human and animal populations. STEM is not a model or a tool designed for a specific disease; it is a flexible, modular framework supporting exchange and integration of community models, reusable plug‐in components, and denominator data, available to researchers worldwide.

Temperature-Dependent Growth Characteristics of Bacillus thuringiensis in a Ratatouille Food Model

ABSTRACT

In contrast to Bacillus cereus, the role of Bacillus thuringiensis in foodborne illness has been controversially discussed. As B. thuringiensis-based biopesticides containing a mixture of crystal toxins and viable spores are widely used, a current European Food Safety Authority opinion underlines the need for additional data to enable risk assessment. However, it is currently poorly understood if B. thuringiensis is able to multiply in food, which is crucial to sound risk assessment. Therefore, the aim of this study was to investigate growth of selected B. thuringiensis strains from food and insecticides in a ratatouille food model. To this end, the growth parameters of three B. thuringiensis strains were determined: insecticide strain ABTS-351 (CH_119, B. thuringiensis serovar kurstaki), insecticide strain ABTS-1857 (CH_121, B. thuringiensis serovar aizawai), and CH_48 (wild-type B. thuringiensis isolated from rosemary), producing extremely high levels of enterotoxins. After an initial drop in colony counts, we observed a statistically significant growth for the tested B. thuringiensis strains between 6 and 24 h at 22, 30, and 37°C, conditions mimicking prolonged holding times. We were also able to show that the enterotoxin overproducer CH_48 can grow up to 108 CFU/g in the ratatouille matrix within 24 h at 37°C. The two midlevel enterotoxin formers ABTS-351 (CH_119) and ABTS-1857 (CH_121) isolated from biopesticides exhibited growth between 6 and 24 h, with one of the strains growing to 107 CFU/g. To our knowledge, this is the first study providing evidence of B. thuringiensis growth in a food model with intact competitive flora. Our findings suggest strain-specific variation and stress the complexity of assessing the risk related to B. thuringiensis in food, indicating that some strains can represent a risk to consumer health when vegetable-based foods are stored under conditions of prolonged temperature abuse.

HIGHLIGHTS

Application of data science in risk assessment and early warning

The food supply chain has been recognised by the EU as a critical infrastructure, and its complexity is the main cause of vulnerability. Depending on the food matrix, natural and/or deliberate contamination, food-borne diseases or even food fraud incidents may occur worldwide. Consequently, robust predictive models and/or software tools are needed to support decision-making and mitigating risks in an efficient and timely manner. In this frame, the fellow participated in data collection and analysis tasks, so as to provide additional predictive models. The working programme, covered a wide range of aspects related to risk assessment including identification of emerging risks (quantitative), microbiological risk assessment, authenticity assessment, spatio-temporal epidemiological modelling and database formation for hosting predictive microbial models. The training and close integration, in the open-source, in-house (German Federal Institute for Risk Assessment (BfR)) developed software tools under the framework of FoodRisk-Labs (https://foodrisklabs.bfr.bund.de.) for data analysis, predictive microbiology, quantitative microbiological risk assessment and automatic data retrieval purposes allowed for the independent use. Moreover, the fellow actively contributed to the update of the upcoming Yersinia enterocolitica risk assessment, and also in authenticity assessment of edible oils. Over the course of the year, the fellow was closely involved in international and national research projects with experts in the above-mentioned disciplines. Lastly, he consolidated his acquired knowledge by presenting his scientific work to conferences, and BfR-internal meetings.

Application of data science in risk assessment and early warning

The currently applied approaches, procedures and tools used for the identification of emerging risks vary greatly among Member States of the EU. EFSA established a structured approach for emerging risk identification that mainly consists of systematically searching, collecting, collating and analysing information and data. In addition, EFSA concluded that new methodologies and tools are needed to facilitate efficient and transparent sharing of data, knowledge and methods in the field of emerging risk identification between Member States. As the result of an open call issued by EFSA, the ‘Determination and metrics of emerging risks’ (DEMETER) project was established in spring 2017 to support current and future procedures for identification of emerging risks. As the Bundesinstitut für Risikobewertung (BfR) hosting site is involved in the DEMETER project, as well as in several other software development activities in the area of quantitative microbiological risk assessment, the fellow had the opportunity to play an active role in the project work and development of the running DEMETER project. The training and close integration in the project team enabled the fellow to make significant contributions, e.g. with the creation of new open source data processing workflows and by contributing to the Emerging Risk Knowledge Exchange Platform (ERKEP) Framework Concept Note. Besides DEMETER, the fellow participated in other activities of the Unit for Food Technologies, Supply Chains and Food Defence, including testing and applying several BfR open source software tools which had been developed in previous projects and that are used in microbiological risk assessment (e.g. Predictive Microbial Modelling Lab (PMM‐Lab)) or as automatic data retrieval systems (e.g. SiLeBAT NewsRadar) – see https://foodrisklabs.bfr.bund.de.

FoodChain-Lab: A Trace-Back and Trace-Forward Tool Developed and Applied during Food-Borne Disease Outbreak Investigations in Germany and Europe

FoodChain-Lab is modular open-source software for trace-back and trace-forward analysis in food-borne disease outbreak investigations. Development of FoodChain-Lab has been driven by a need for appropriate software in several food-related outbreaks in Germany since 2011. The software allows integrated data management, data linkage, enrichment and visualization as well as interactive supply chain analyses. Identification of possible outbreak sources or vehicles is facilitated by calculation of tracing scores for food-handling stations (companies or persons) and food products under investigation. The software also supports consideration of station-specific cross-contamination, analysis of geographical relationships, and topological clustering of the tracing network structure. FoodChain-Lab has been applied successfully in previous outbreak investigations, for example during the 2011 EHEC outbreak and the 2013/14 European hepatitis A outbreak. The software is most useful in complex, multi-area outbreak investigations where epidemiological evidence may be insufficient to discriminate between multiple implicated food products. The automated analysis and visualization components would be of greater value if trading information on food ingredients and compound products was more easily available.

Towards a Food Safety Knowledge Base Applicable in Crisis Situations and Beyond

In case of contamination in the food chain, fast action is required in order to reduce the numbers of affected people. In such situations, being able to predict the fate of agents in foods would help risk assessors and decision makers in assessing the potential effects of a specific contamination event and thus enable them to deduce the appropriate mitigation measures. One efficient strategy supporting this is using model based simulations. However, application in crisis situations requires ready-to-use and easy-to-adapt models to be available from the so-called food safety knowledge bases. Here, we illustrate this concept and its benefits by applying the modular open source software tools PMM-Lab and FoodProcess-Lab. As a fictitious sample scenario, an intentional ricin contamination at a beef salami production facility was modelled. Predictive models describing the inactivation of ricin were reviewed, relevant models were implemented with PMM-Lab, and simulations on residual toxin amounts in the final product were performed with FoodProcess-Lab. Due to the generic and modular modelling concept implemented in these tools, they can be applied to simulate virtually any food safety contamination scenario. Apart from the application in crisis situations, the food safety knowledge base concept will also be useful in food quality and safety investigations.

DEVELOPMENT OF AN ANNOTATION SCHEME FOR STANDARDIZED DESCRIPTION OF MATHEMATICAL MODELS IN THE FIELD OF PLANT PROTECTION

Mathematical models on properties and behavior of harmful organisms in the food chain are an increas- ingly relevant approach of the agriculture and food industry. As a consequence, there are many efforts to develop biological models in science, economics and risk assessment nowadays. However, there is a lack of international harmonized standards on model annotation and model formats, which would be neces- sary to set up efficient tools supporting broad model application and information exchange. There are some established standards in the field of systems biology, but there is currently no corresponding provi- sion in the area of plant protection. This work therefore aimed at the development of an annotation scheme using domain-specific metadata. The proposed scheme has been validated in a prototype implementation of a web-database model repository. This prototypic community resource currently contains models on aflatoxin secreting fungal Aspergillus flavus in maize, as these models have a high relevance to food safety and economic impact. Specifically, models describing biological processes of the fungus (growth, Aflatoxin secreting), as well as dose-response- and carry over models were included. Furthermore, phenological models for maize were integrated as well. The developed annotation scheme is based on the well-established data exchange format SBML, which is broadly applied in the field of systems biology. The identified example models were annotated according to the developed scheme and entered into a Web-table (Google Sheets), which was transferred to a web based demonstrator available at https://sites.google.com/site/test782726372685/. By implementation of a software demonstrator it became clear that the proposed annotation scheme can be applied to models on plant pathogens and that broad adoption within the domain could promote communication and application of mathematical models.

A generic open-source software framework supporting scenario simulations in bioterrorist crises

Since the 2001 anthrax attack in the United States, awareness of threats originating from bioterrorism has grown. This led internationally to increased research efforts to improve knowledge of and approaches to protecting human and animal populations against the threat from such attacks. A collaborative effort in this context is the extension of the open-source Spatiotemporal Epidemiological Modeler (STEM) simulation and modeling software for agro- or bioterrorist crisis scenarios. STEM, originally designed to enable community-driven public health disease models and simulations, was extended with new features that enable integration of proprietary data as well as visualization of agent spread along supply and production chains. STEM now provides a fully developed open-source software infrastructure supporting critical modeling tasks such as ad hoc model generation, parameter estimation, simulation of scenario evolution, estimation of effects of mitigation or management measures, and documentation. This open-source software resource can be used free of charge. Additionally, STEM provides critical features like built-in worldwide data on administrative boundaries, transportation networks, or environmental conditions (eg, rainfall, temperature, elevation, vegetation). Users can easily combine their own confidential data with built-in public data to create customized models of desired resolution. STEM also supports collaborative and joint efforts in crisis situations by extended import and export functionalities. In this article we demonstrate specifically those new software features implemented to accomplish STEM application in agro- or bioterrorist crisis scenarios.

Studies on the effect of an Enterococcus faecium probiotic on T cell populations in peripheral blood and intestinal epithelium and on the susceptibility to Salmonella during a challenge infection with Salmonella Typhimurium in piglets

Although Enterococcus faecium is used as a probiotic feed supplement in animal production, feeding of the bacterium to piglets resulted in a more severe infection with Salmonella Typhimurium DT104 during a challenge experiment. To enlighten the mode of action by which E. faecium affected the piglets' health, we investigated the influence of the probiotic bacterium on the development of intestinal and circulating immune cells during a challenge experiment with S. Typhimurium DT104. To minimise varying impacts of the maternal immunity on the course of infection, only piglets were implemented that descended from Salmonella-free sows. In addition, the potency of purified blood and intraepithelial immune cells to control the growth of Salmonella was tested in vitro. In animals treated with E. faecium, a reduction of intraepithelial CD8alphabeta T cells, reduced circulating CD8alphabeta T cells and a less efficient control of intracellular Salmonella growth, mediated by peripheral blood mononuclear cells, were observed.

Thermal stability of hepatitis E virus assessed by a molecular biological approach

Background

Hepatitis E virus (HEV) is a pathogen of emerging concern in industrialized countries. The consumption of wild boar meat has been identified as one risk factor for autochthonous HEV infections. Only limited information is available about thermal stability of HEV, mainly due to the lack of rapid and efficient cell culture systems for measurement of HEV infectivity.

Methods

A molecular biological method was implemented in order to distinguish disassembled from intact viral particles using RNase treatment followed by quantitative real-time RT-PCR. The method was applied to a wild boar liver suspension containing HEV genotype 3.

Results

Time-course analyses indicated that the decline of protected RNA could be described by a biphasic model with an initial decrease followed by a stationary phase. The stationary phase was reached after 1 hour at 4°C, 3 days at 22°C and 7 days at 37°C with log reductions of 0.34, 0.45 and 1.24, respectively. Protected RNA was detectable until the end of the experiments at day 50 or 70. Heat exposure for 1 minute resulted in a log reduction of 0.48 at 70°C and increased with higher temperatures to 3.67 at 95°C. Although HEV infectivity titration by inoculation of the liver suspension onto three cell lines did not succeed, the results of the RNase-based method are in accordance with published cell culture-based data.

Conclusions

Measurement of intact viral particles using the RNase-based method may provide data on the stability of RNA viruses when cell culture-based infectivity titrations are not efficient or not available. The method enables processing of large sample numbers and may be suitable to estimate stability of HEV in different types of food.

Antimicrobial resistances do not affect colonization parameters of intestinal E. coli in a small piglet group

BACKGROUND

Although antimicrobial resistance and persistence of resistant bacteria in humans and animals are major health concerns worldwide, the impact of antimicrobial resistance on bacterial intestinal colonization in healthy domestic animals has only been rarely studied. We carried out a retrospective analysis of the antimicrobial susceptibility status and the presence of resistance genes in intestinal commensal E. coli clones from clinically healthy pigs from one production unit with particular focus on effects of pheno- and/or genotypic resistance on different nominal and numerical intestinal colonization parameters. In addition, we compared the occurrence of antimicrobial resistance phenotypes and genotypes with the occurrence of virulence associated genes typical for extraintestinal pathogenic E. coli.

RESULTS

In general, up to 72.1% of all E. coli clones were resistant to ampicillin, chloramphenicol, kanamycin, streptomycin, sulfamethoxazole or tetracycline with a variety of different resistance genes involved. There was no significant correlation between one of the nominal or numerical colonization parameters and the absence or presence of antimicrobial resistance properties or resistance genes. However, there were several statistically significant associations between the occurrence of single resistance genes and single virulence associated genes.

CONCLUSION

The demonstrated resistance to the tested antibiotics might not play a dominant role for an intestinal colonization success in pigs in the absence of antimicrobial drugs, or cross-selection of other colonization factors e.g. virulence associated genes might compensate "the cost of antibiotic resistance". Nevertheless, resistant strains are not outcompeted by susceptible bacteria in the porcine intestine.

Effects of Bacillus cereus var. toyoi on immune parameters of pregnant sows

Changing immune parameters during pregnancy have previously been reported in humans and cattle, and have been suggested to contribute to increased susceptibility to infections. However, data regarding immune parameters during pregnancy in sows are rare. In this study, we investigated the peripartal immune status of sows using phenotypical (FACS analysis) as well as functional (proliferation assays, cytokine analysis) parameters of peripheral blood mononuclear cells (PBMCs) in pregnant sows. In previous studies, we reported a modulation of the immune system after feed supplementation of the probiotic Bacillus cereus var. toyoi in piglets [Schierack, P., Wieler, L.H., Taras, D., Herwig, V., Tachu, B., Hlinak, A., Schmidt, M.F., Scharek, L., 2007. Bacillus cereus var. toyoi enhanced systemic immune response in piglets. Vet. Immunol. Immunopathol. 118, 1-11]. Here, we extended these previous studies to include investigations of possible probiotic effects on the peripartal immune status of sows and their reproductivity. We show that immune parameters of sows change during pregnancy, the proliferative response of PBMCs to several bacterial antigens in control animals decreased from days 90 to 30 ante partum. Relative numbers (%) of CD3+CD8+, CD4+, cytotoxic T, CD14+ and CD21+ cells were reduced compared to non-pregnant sows. In contrast, the proliferative response of PBMCs of probiotic-treated sows increased during pregnancy. Bacterial antigens primarily stimulated the proliferation of naïve CD21+ cells and the relative CD21+ cell numbers were elevated in the probiotic group in the absence of effects on other immune cell populations. The clinical and microbial status of both control and probiotic sows was similar, excluding pre-existing health problems or infections as responsible for the immunological changes, and feed supplementation also had no significant effects on reproductivity. The results suggest that the probiotic B. cereus var. toyoi can alter the proliferative response of lymphocytes and affects the immune cell population ratios of pregnant sows. How and to what extent this may affect health and reproductivity should be the focus of further studies.

Impact of the probiotic bacteria Enterococcus faecium NCIMB 10415 (SF68) and Bacillus cereus var. toyoi NCIMB 40112 on the development of serum IgG and faecal IgA of sows and their piglets

To examine the influence of two different probiotic bacteria on the humoral immune system of swine, two animal studies were carried out with sows and their litters. The sows' feed was supplemented with either Enterococcusfaecium NCIMB 10415 (SF68) or Bacillus cereus var. toyoi NCIMB 40112 beginning early in pregnancy. The total IgA content in the faeces as well as the total IgG concentration in the blood of the sows was recorded before and after weaning. The same parameters were determined in the blood and faeces of the piglets. In sows, only feed supplementation with B. cereus led to a clear increase in faecal IgA. Serum IgG levels were not significantly affected by any probiotic feeding in sows. In piglets, the group that was fed B. cereus showed significantly higher faecal IgA levels shortly before weaning, whereas in the E. faecium group, a significant decrease in IgA levels was observed one week after weaning. In both probiotic fed groups the post-weaning IgG levels were significantly decreased compared to the respective control groups. We conclude that B. cereus var. toyoi feed supplementation led to an increased intestinal IgA secretion both in sows and piglets. This effect could be related to a more successful mucosal defence which in turn led to a lower level in systemic IgG production in piglets after weaning.

Virulence genotype of Pasteurella multocida strains isolated from different hosts with various disease status

To learn more about the molecular biology of Pasteurella multocida 289 strains isolated from various clinically healthy and diseased hosts were examined for capsule biosynthesis genes (capA, B, D, E, and F) and 14 virulence associated genes by PCR and DNA-DNA-hybridization. As expected, capsule type A strains were highly adapted to bovines (92.3%) and poultry (85.7%) while we mainly found capA (34.9%)- and capD (58.1%)-positive strains in swine. A noticeable amount of capD-positive strains also originated from small ruminants (34.9%) and capF was detected in wild type strains from diseased cattle (2.2%) and cats (7.4%). None of the isolates harboured capE, while capB was exclusively found in all strains from buffaloes. Nearly all isolates showed a combination of genes encoding outer membrane proteins, colonization factors, iron aquisition factors and superoxid-dismutases without any clue for host specificity. In contrast, the transferrin binding protein encoding gene tbpA (31.5%) was limited to ruminant strains and only 37.0% of all P. multocida strains harboured pfhA, coding for a filamentous hemagglutinin, supposed to be a putative adhesion- und serum resistance factor. PfhA revealed a strong positive association to the outcome of disease in bovine hosts and in combination with toxA to that in swine. The dermonecrotoxin encoding toxA, present in 12.5% of all strains, was detected in isolates from swine, small ruminants, cattle, and poultry. A significant association to the disease status, however, was only existent in swine, although with 66.7% we found a notably high prevalence of the toxin gene among strains from small ruminants. The genes toxA, tbpA and pfhA as well as capsule biosynthesis genes are supposed to be important epidemiological marker genes for characterizing P. multocida field strains.

Identification of Noncanonical Melanoma-Associated T Cell Epitopes for Cancer Immunotherapy

The identification of tumor-associated T cell epitopes has contributed significantly to the understanding of the interrelationship of tumor and immune system and is instrumental in the development of therapeutic vaccines for the treatment of cancer. Most of the known epitopes have been identified with prediction algorithms that compute the potential capacity of a peptide to bind to HLA class I molecules. However, naturally expressed T cell epitopes need not necessarily be strong HLA binders. To overcome this limitation of the available prediction algorithms we established a strategy for the identification of T cell epitopes that include suboptimal HLA binders. To this end, an artificial neural network was developed that predicts HLA-binding peptides in protein sequences by taking the entire sequence context into consideration rather than computing the sum of the contribution of the individual amino acids. Using this algorithm, we predicted seven HLA A*0201-restricted potential T cell epitopes from known melanoma-associated Ags that do not conform to the canonical anchor motif for this HLA molecule. All seven epitopes were validated as T cell epitopes and three as naturally processed by melanoma tumor cells. T cells for four of the new epitopes were found at elevated frequencies in the peripheral blood of melanoma patients. Modification of the peptides to the canonical sequence motifs led to improved HLA binding and to improved capacity to stimulate T cells.

Physical and transcriptional map of the critical region for keratolytic winter erythema (KWE) on chromosome 8p22-p23 between D8S550 and D8S1759

Keratolytic winter erythema is an autosomal dominant skin disorder characterised by erythema, hyperkeratosis, and peeling of the skin of the palms and soles, especially during winter. The keratolytic winter erythema locus has been mapped to human chromosome 8p22-p23. This chromosomal region has also been associated with frequent loss of heterozygosity in different types of cancer. To identify positional candidate genes for keratolytic winter erythema, a BAC contig located between the markers at D8S550 and D8S1695 was constructed and sequenced. It could be extended to D8S1759 by a partially sequenced BAC clone identified by database searches. In the 634 404 bp contig 13 new polymorphic microsatellite loci and 46 single nucleotide and insertion/deletion polymorphisms were identified. Twelve transcripts were identified between D8S550 and D8S1759 by exon trapping, cDNA selection, and sequence analyses. They were localised on the genomic sequence, their exon/intron structure was determined, and their expression analysed by RT-PCR. Only one of the transcripts corresponds to a known gene, encoding B-lymphocyte specific tyrosine kinase, BLK. A putative novel myotubularin-related protein gene (MTMR8), a potential human homologue of the mouse acyl-malonyl condensing enzyme gene (Amac1), and two transcripts showing similarities to the mouse L-threonine 3-dehydrogenase gene and the human SEC oncogene, respectively, were identified. The remaining seven transcripts did not show similarities to known genes. There were no potentially pathogenic mutations identified in any of these transcripts in keratolytic winter erythema patients.