Introducing the Rapid Alert Supply Network Extractor (RASNEX) tool to mine supply chain information from food and feed contamination notifications in Europe.

BACKGROUND: During food or feed contamination events, it is of utmost importance to ensure their rapid resolution to minimize impact on human health, animal health and finances. The existing Rapid Alert System for Food and Feed (RASFF) is used by the European Commission, national competent authorities of member countries and the European Food Safety Authority to report information on any direct or indirect human health risk arising from food or feed, or serious risks to animal health or the environment in relation to feed. Nevertheless, no methods exist to to collectively evaluate this vast source of supply chain information. METHODS: To aid in the extraction, evaluation and visualization of the data in RASFF notifications, we present the Rapid Alert Supply Network Extractor (RASNEX) open-source tool available from https://doi.org/10.5281/zenodo.4322555 freely. Among RASNEX's functions is the graphical mapping of food and feed supply chain operators implicated in contamination events. RASNEX can be used during ongoing events as a support tool for risk analysis using RASFF notifications as input. RESULTS: In a first use case, we showcase the functionality of RASNEX with the RASFF notification on a 2017/2018 contamination event in eggs caused by the illegal use of fipronil. The information in this RASFF notification is used to visualize nine different flows of main and related food products. In a second use case, we combine RASFF notifications from different types of food safety hazards (Salmonella spp., fipronil and others) to obtain wider coverage of the visualized egg supply network compared to the first use case. Actors in the egg supply chain were identified mainly for Italy, Poland and Benelux. Other countries (although involved in the egg supply chain) were underrepresented. CONCLUSIONS: We hypothesize that biases may be caused by inconsistent RASFF reporting behaviors by its members. These inconsistencies may be counteracted by implementing standardized decision-making tools to harmonize decisions whether to launch a RASFF notification, in turn resulting in a more uniform future coverage across European food and feed supply chains with RASNEX.

Cluster analysis of resistance combinations in Escherichia coli from different human and animal populations in Germany 2014-2017.

Recent findings on Antibiotic Resistance (AR) have brought renewed attention to the comparison of data on AR from human and animal sectors. This is however a major challenge since the data is not harmonized. This study performs a comparative analysis of data on resistance combinations in Escherichia coli (E. coli) from different routine surveillance and monitoring systems for human and different animal populations in Germany. Data on E. coli isolates were collected between 2014 and 2017 from human clinical isolates, non-clinical animal isolates from food-producing animals and food, and clinical animal isolates from food-producing and companion animals from national routine surveillance and monitoring for AR in Germany. Sixteen possible resistance combinations to four antibiotics-ampicillin, cefotaxime, ciprofloxacin and gentamicin-for these populations were used for hierarchical clustering (Euclidian and average distance). All analyses were performed with the software R 3.5.1 (Rstudio 1.1.442). Data of 333,496 E. coli isolates and forty-one different human and animal populations were included in the cluster analysis. Three main clusters were detected. Within these three clusters, all human populations (intensive care unit (ICU), general ward and outpatient care) showed similar relative frequencies of the resistance combinations and clustered together. They demonstrated similarities with clinical isolates from different animal populations and most isolates from pigs from both non-clinical and clinical isolates. Isolates from healthy poultry demonstrated similarities in relative frequencies of resistance combinations and clustered together. However, they clustered separately from the human isolates. All isolates from different animal populations with low relative frequencies of resistance combinations clustered together. They also clustered separately from the human populations. Cluster analysis has been able to demonstrate the linkage among human isolates and isolates from various animal populations based on the resistance combinations. Further analyses based on these findings might support a better one-health approach for AR in Germany.

Two consecutive large outbreaks of Salmonella Muenchen linked to pig farming in Germany, 2013 to 2014: Is something missing in our regulatory framework?

In 2013, raw pork was the suspected vehicle of a large outbreak (n = 203 cases) of Salmonella Muenchen in the German federal state of Saxony. In 2014, we investigated an outbreak (n = 247 cases) caused by the same serovar affecting Saxony and three further federal states in the eastern part of Germany. Evidence from epidemiological, microbiological and trace-back investigations strongly implicated different raw pork products as outbreak vehicles. Trace-back analysis of S. Muenchen-contaminated raw pork sausages narrowed the possible source down to 54 pig farms, and S. Muenchen was detected in three of them, which traded animals with each other. One of these farms had already been the suspected source of the 2013 outbreak. S. Muenchen isolates from stool of patients in 2013 and 2014 as well as from food and environmental surface swabs of the three pig farms shared indistinguishable pulsed-field gel electrophoresis patterns. Our results indicate a common source of both outbreaks in the primary production of pigs. Current European regulations do not make provisions for Salmonella control measures on pig farms that have been involved in human disease outbreaks. In order to prevent future outbreaks, legislators should consider tightening regulations for Salmonella control in causative primary production settings.

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.

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.

Development of a comparative risk ranking system for agents posing a bioterrorism threat to human or animal populations.

Various systems for prioritizing biological agents with respect to their applicability as biological weapons are available, ranging from qualitative to (semi)quantitative approaches. This research aimed at generating a generic risk ranking system applicable to human and animal pathogenic agents based on scientific information. Criteria were evaluated and clustered to create a criteria list. Considering availability of data, a number of 28 criteria separated by content were identified that can be classified in 11 thematic areas or categories. Relevant categories contributing to probability were historical aspects, accessibility, production efforts, and possible paths for dispersion. Categories associated with impact are dealing with containment measures, availability of diagnostics, preventive and treatment measures in human and animal populations, impact on society, human and veterinary public health, and economic and ecological consequences. To allow data-based scoring, each criterion was described by at least 1 measure that allows the assignment of values. These values constitute quantities, ranges, or facts that are as explicit and precise as possible. The consideration of minimum and maximum values that can occur due to natural variations and that are often described in the literature led to the development of minimum and maximum criteria and consequently category scores. Missing or incomplete data, and uncertainty resulting therefrom, were integrated into the scheme via a cautious (but not overcautious) approach. The visualization technique that was used allows the description and illustration of uncertainty on the level of probability and impact. The developed risk ranking system was evaluated by assessing the risk originating from the bioterrorism threat of the animal pathogen bluetongue virus, the human pathogen Enterohemorrhagic Escherichia coli O157:H7, the zoonotic Bacillus anthracis, and Botulinum neurotoxin.

Mapping discontinuous protein-binding sites via structure-based peptide libraries: combining in silico and in vitro approaches.

To perform their various functions, protein surfaces often have to interact with each other in a specific way. Usually, only parts of a protein are accessible and can act as binding sites. Because proteins consist of polypeptide chains that fold into complex three-dimensional shapes, binding sites can be divided into two different types: linear sites that follow the primary amino acid sequence and discontinuous binding sites, which are made up of short peptide fragments that are adjacent in spatial proximity. Such discontinuous binding sites dominate protein-protein interactions, but are difficult to identify. To meet this challenge, we combined a computational, structure-based approach and an experimental, high-throughput method. SUPERFICIAL is a program that uses protein structures as input and generates peptide libraries to represent the protein's surface. A large number of the predicted peptides can be simultaneously synthesised applying the SPOT technology. The results of a binding assay subsequently help to elucidate protein-protein interactions; the approach is applicable to any kind of protein. The crystal structure of the complex of hen egg lysozyme with the well-characterised murine IgG1 antibody HyHEL-5 is available, and the complex is known to have a discontinuous binding site. Using SUPERFICIAL, the entire surface of lysozyme was translated into a peptide library that was synthesised on a cellulose membrane using the SPOT technology and tested against the HyHEL-5 antibody. In this way, it was possible to identify two peptides (longest common sequence and peptide 19) that represented the discontinuous epitope of lysozyme.

Trace-back and trace-forward tools developed ad hoc and used during the STEC O104:H4 outbreak 2011 in Germany and generic concepts for future outbreak situations.

The Shiga toxin-producing Escherichia coli O104:H4 outbreak in Germany in 2011 required the development of appropriate tools in real-time for tracing suspicious foods along the supply chain, namely salad ingredients, sprouts, and seeds. Food commodities consumed at locations identified as most probable site of infection (outbreak clusters) were traced back in order to identify connections between different disease clusters via the supply chain of the foods. A newly developed relational database with integrated consistency and plausibility checks was used to collate these data for further analysis. Connections between suppliers, distributors, and producers were visualized in network graphs and geographic projections. Finally, this trace-back and trace-forward analysis led to the identification of sprouts produced by a horticultural farm in Lower Saxony as vehicle for the pathogen, and a specific lot of fenugreek seeds imported from Egypt as the most likely source of contamination. Network graphs have proven to be a powerful tool for summarizing and communicating complex trade relationships to various stake holders. The present article gives a detailed description of the newly developed tracing tools and recommendations for necessary requirements and improvements for future foodborne outbreak investigations.

Is there a typical germinal center? A large-scale immunohistological study on the cellular composition of germinal centers during the hapten-carrier-driven primary immune response in mice.

Germinal centers (GCs) are complex, multicell-type, transient structures that form in secondary lymphatic tissues in response to T cell-dependent stimulation. This process is crucial to the adaptive immune response because it is the source of affinity maturation and long-lived B cell memory. Our previous studies showed that the growth of murine splenic GCs is nonsynchronized, involving broad-volume distributions of individual GCs at any time. This raises the question whether such a thing as a typical GC exists. To address this matter, we acquired large-scale confocal data on GCs throughout the course of the 2-phenyl-5-oxazolone chicken serum albumin-driven primary immune response in BALB/c mice. Semiautomated image analysis of 3457 GC sections revealed that, although there is no typical GC in terms of size, GCs have a typical cellular composition in that the cell ratios of resident T cells, macrophages, proliferating cells, and apoptotic nuclei are maintained during the established phase of the response. Moreover, our data provide evidence that the dark zone (DZ) and light zone (LZ) compartments of GCs are about the same size and led us to estimate that the minimal cell loss rate in GCs is 3% per hour. Furthermore, we found that the population of GC macrophages is larger and more heterogeneous than previously thought, and that despite enrichment of T cells in the LZ, the DZ of murine splenic GCs is not poor in T cells. DZ and LZ differ in the T cell-to-macrophage ratio rather than in the density of T cells.

Affinity maturation of B cells involves not only a few but a whole spectrum of relevant mutations.

Affinity maturation of B lymphocytes within germinal centers involves both diversification of their B-cell receptors (BCRs) by somatic hypermutation (SHM) and a crucial receptor-mediated selection step. However, in contrast to recent advances in revealing the molecular mechanism of SHM, the fundamentals of the selection process are still poorly understood, i.e. it is often not clear how and how many mutations contribute to improving a BCR during the response against a given antigen. A general drawback in assessing the mutations relevant to the selection process is the difficult task of rating the relative contributions of selection and intrinsic biases to the experimentally observed mutation patterns of BCRs. The approach proposed here is premised on statistical comparison of the frequency distributions of nucleotide substitutions as observed in datasets of hypermutated BCRs against their frequency distribution expected under the null hypothesis of no selection. Thereby, we show that the spectrum of mutations relevant to maturation of canonical anti-(4-hydroxy-3-nitrophenyl)acetyl BCRs is much broader than previously acknowledged, going beyond the scope of single key mutations. Moreover, our results suggest that maturation not only involves selection by means of affinity but likewise expression and stabilization of BCRs.

Broad volume distributions indicate nonsynchronized growth and suggest sudden collapses of germinal center B cell populations.

Immunization with a T cell-dependent Ag leads to the formation of several hundred germinal centers (GCs) within secondary lymphoid organs, a key process in the maturation of the immune response. Although prevailing perceptions about affinity maturation intuitively assume simultaneous seeding, growth, and decay of GCs, our previous mathematical simulations led us to hypothesize that their growth might be nonsynchronized. To investigate this, we performed computer-aided three-dimensional reconstructions of splenic GCs to measure size distributions at consecutive time points following immunization of BALB/c mice with a conjugate of 2-phenyl-oxazolone and chicken serum albumin. Our analysis reveals a broad volume distribution of GCs, indicating that individual GCs certainly do not obey the average time course of the GC volumes and that their growth is nonsynchronized. To address the cause and implications of this behavior, we compared our empirical data with simulations of a stochastic mathematical model that allows for frequent and sudden collapses of GCs. Strikingly, this model succeeds in reproducing the empirical average kinetics of GC volumes as well as the underlying broad size distributions. Possible causes of GC B cell population collapses are discussed in the context of the affinity-maturation process.

Recirculation of germinal center B cells: a multilevel selection strategy for antibody maturation.

Optimization of antibody affinity is a hallmark of the humoral immune response. It takes place in hundreds of transient microstructures called germinal centers (GCs). Their function and time-dependent behavior are subjects of active investigation. According to a generally accepted notion, their individual kinetics follows the average kinetics of all GCs present in the observed lymphatic tissue. In this review, we challenge this view and point out, with the help of mathematical simulations, that inferring the kinetics of individual GCs from cross-sectional evaluation of GC kinetics is virtually impossible. Thus, the time course of individual GCs is open to conjecture. For instance, one possible interpretation is that GCs exist for a time span considerably shorter than that of the observed average kinetics. We explore the implications of different temporal organizations of GCs in the light of the hypothesis that GC B-cell emigrants recolonize GC niches. This assumption leads to a view where GCs work in parallel but are linked by recirculation of B-cell emigrants. In this view, interleaved global and local competition provide for an implementation of multiple levels of B-cell selection in affinity maturation. The concepts of iteration, all-or-none behavior, and phasic mutation schedule are discussed in the light of this hypothesis.

Influence of antigen on the development of MALT lymphoma.

Mucosa-associated lymphoid tissue (MALT) B-cell lymphomas develop in the context of autoimmune or chronic inflammations like Helicobacter pylori-induced gastritis. Remission of most gastric MALT lymphomas after eradication of H pylori links tumor cell proliferation to antigen-induced inflammation and the need for antigenic contact. Furthermore, the tumor cells correspond to antigen-activated memory B cells. To investigate the reactivity of the tumor immunoglobulins we employed in vitro-generated antibodies identical to those produced by MALT lymphoma cells. The immunoglobulin rearrangements of 7 MALT lymphomas were amplified, cloned, and expressed as single-chain fragment variable (scFv) antibodies. Antigen specificity of these 7 scFvs was analyzed by immunohistochemical staining of various normal, reactive, and malignant human tissues. Also, an expression library comprising approximately 30,000 proteins from human fetal brains (protein filter) and a peptide library were screened. One scFv stained a subpopulation of tonsillar plasma cells in immunohistochemical studies. On protein filters this scFv recognized the plasma cell-related protein Ufc1. Peptide library screening identified 9 peptides as binding partners of an additional scFv. The majority of MALT lymphoma immunoglobulins studied, however, showed no reactivity against antigens, indicating that the tumor immunoglobulins do not play a significant role in stimulation and proliferation of the MALT lymphoma tumor cells.

SPOT synthesis: reliability of array-based measurement of peptide binding affinity.

Peptide arrays prepared by the SPOT synthesis technology have emerged as a proteomic tool to study molecular recognition and identify biologically active peptides. However, it was previously not clear how accurately signal intensities obtained by probing peptide arrays for protein binding really reflect the dissociation constants of the protein-peptide complexes. Using the monoclonal antibody CB4-1 as a model system, we systematically compared dissociation constants of antibody-peptide complexes with signal intensities obtained using the SPOT technology. By analyzing a set of peptides possessing different affinities to the antibody, we determined the strengths of the SPOT screening method. The accuracy of the measured results was improved by taking regional trends in the membrane surface into account. A model based on the mass action law compares well with the experimental results. Interestingly, the applied concentrations of the binding partners do not directly correspond to the effective concentrations in the assay. We show that the SPOT technology is an accurate method for assigning the spots' measured signal intensities to three different binding affinity classes. The dissociation constants of the intermediate region were found to be between pK(dis)=5 and pK(dis)=7. Altering the experimental parameters causes a directed change of this region.

Expression levels of the putative zinc transporter LIV-1 are associated with a better outcome of breast cancer patients.

We investigated the expression pattern of the breast cancer associated gene LIV-1 on mRNA and protein level in 111 human breast cancer patients by in situ hybridization as well as immunohistochemistry and focused on the unknown potential of LIV-1 expression levels as a prognostic marker. To our knowledge, this is the first study on endogenous LIV-1 protein expression. Results of our study indicate that LIV-1 mRNA and protein expression levels are only weakly correlated, suggesting posttranscriptional regulatory mechanisms. Furthermore, LIV-1 mRNA quantity in combination with a positive ER status seem to represent a better marker than the progesterone receptor status according to the prognostic significance for relapse free survival (RFS). A negative correlation of LIV-1 protein levels with tumor size, grade and stage reflects an association of LIV-1 protein expression with less aggressive tumors. High LIV-1 protein expression seems to be associated with a longer relapse free and overall survival in breast cancer patients with invasive ductal carcinoma. This association, however, seems to be dependent from other prognostic markers. Our data suggest that LIV-1 is a promising candidate for a novel marker for breast cancer patients with better outcome. Furthermore, our study presents a revised cDNA sequence of LIV-1 and demonstrates the localization of endogenous LIV-1 in the endoplasmic reticulum.