The Friedrich Loeffler Institute (FLI), is the Federal Institute for Animal Health of Germany, that country's leading animal disease center. The institute was founded in 1910 and named for its founder Friedrich Loeffler in 1952. The FLI is situated on the Isle of Riems, which belongs to the City of Greifswald. Riems is a very small island that can be reached via a dam, which can be closed off in case of an outbreak. Due to these circumstances, Riems posed the perfect location for one of the most modern animal health research facilities in the world.The Friedrich Loeffler Institute is directly subordinated to the German Ministry of Food, Agriculture and Consumer Protection. Its main subject is the thorough study of livestock health and other closely related subjects including molecular biology, virus diagnostics, immunology, and epidemiology. Federal laws of Germany hold the FLI responsible for national and international animal disease control; it also poses the international reference lab for several viral diseases. The institute publishes its research, and cooperates with other national and international institutions and researchers.Among the animal diseases under research are for instance foot and mouth disease, mad cow disease, and avian influenza.Currently, 330 people work for the FLI, and an additional 140 will be employed upon completion of the construction work. 260 Million Euros are spent by the Federal Government to build new laboratories and barns.As part of this extension, in 2010 the Riems Institute completed Biosafety level 4 laboratory facilities, which enable research activities on the most dangerous of viruses—one of four such facilities in Germany.
Animal listeriosis is a sporadic bacterial infection caused by Listeria (L.) monocytogenes and L. ivanovii. In Germany, only listeriosis caused by L. monocytogenes is considered a notifiable disease. The objective of this report is to analyze official surveillance data on animal listeriosis in Germany from 2024 to 2025 to assess the epidemiological situation and the spatiotemporal distribution of this One Health relevant disease. A total of 341 notifications involving 652 affected animals were reported. The highest number of cases occurred in food-producing animals, particularly cattle, followed by sheep and goats. Listeriosis has also been reported in pet animals, wildlife, and poultry. The epidemiological situation and geographical distribution of the disease have remained consistent over the past decade, with the highest incidences in Berlin, Bavaria, and Baden-Wuerttemberg. Listeriae cause disease in a broad range of hosts nationwide. Monitoring listeriosis in animals is crucial for public health and the safety of the food supply. Systematic collection of animal isolates is essential to understand transmission from environmental reservoirs to humans—a currently puzzling link. This knowledge is vital for protecting human health.
The transmission of influenza A virus H5N1 clade 2.3.4.4b from cattle to humans highlights the risk of an H5N1 pandemic. Pre-existing immunity strongly impacts the course and severity of viral infections, making detailed knowledge of antibodies against the spilled-over strain crucial. Here, we assessed humoral immunity against H5N1 A/Texas/37/2024 in H5N1-naive individuals. We performed complementary binding and neutralization assays on 66 individuals and ranked activities among a panel of 76 influenza A virus isolates. We detected low but distinct cross-neutralizing titers against A/Texas/37/2024, with a 3.9- to 15.6-fold reduction compared with selected H1N1 or H3N2 strains. By cloning and characterizing 136 memory B cell-derived monoclonal antibodies, we identified potent A/Texas/37/2024-neutralizing antibodies in five out of six individuals we investigated. These antibodies cross-neutralized H1, competed with antibodies targeting the hemagglutinin (HA) stem, and protected mice from lethal H5N1 challenge. Our findings demonstrate partial pre-existing humoral immunity to A/Texas/37/2024 in H5N1-naive individuals.
Introduction:Q fever, caused by Coxiella burnetii, is a zoonotic disease of global relevance with domestic ruminants as the main reservoirs. Serological diagnosis, especially enzyme-linked immunosorbent assay (ELISA), often suffers from limited sensitivity and specificity due to antigenic variability and cross-reactivity. Scientific goal:In this study, a combined proteomic and literature research approach was used to identify immunoreactive proteins and predict linear B-cell epitopes as alternative diagnostic targets. Methods:Total protein extracts of a C. burnetii field isolate from sheep were separated by two-dimensional gel electrophoresis, and immunoreactive proteins were detected by Western blotting using pooled sheep sera obtained from various flocks with known Q fever status. Immunoreactive proteins were identified by LC-MS/MS and used for linear B-cell epitope prediction for peptide synthesis. Peptides (n = 30) were initially screened by fluorescent ELISA against nine field serum pools (90 individual sera), and the most promising peptides (n = 15) were individually tested with 79 single sera. Diagnostic performance was assessed by receiver operating characteristic (ROC) analysis and by a multi-peptide rule ("positive if ≥1 peptide reactive"). Results:A total of 156 seroreactive proteins, including 51 previously reported antigens, were detected, among others, Com1, CBU_0482, and Mip. Although the selected 15 peptides showed a specific reaction with pooled sera, they showed limited diagnostic performance with an area under the curve (AUC) of 0.5-0.7 when using single serum samples (n = 79). Multi-peptide combinations (6-8 peptides) increased sensitivity (Se) to 80% and specificity (Sp) to 75%. Discussion:Although single peptides lacked discriminatory power, multi-epitope combinations reached acceptable accuracy and may be used as a complementary tool for commercial ELISAs. However, larger bioinformatic approaches and validation studies are required to identify specific peptides of high diagnostic accuracy.
The landscape of emerging zoonoses is being rapidly reshaped by concurrent climate change, environmental transformation, and biodiversity loss. These pressures can alter host populations, pathogen dynamics, and human exposure. Yet, continental-scale evidence linking multi-sector drivers to human infection risk for specific rodent-borne diseases remains limited, particularly for hantavirus. To untangle these influences, we assembled the most high-resolution European hantavirus infection dataset to date (2011-2021), combining large datasets on climatic, environmental, biodiversity, and socio-economic aspects to identify the main drivers of human hantavirus transmission. Using machine learning models, we evaluated the best model for predicting the disease risk in Europe and identified the relative importance of each factor in shaping the risk of human hantavirus infection. Our results showed that maximum temperature in the fourth quarter, Gross Domestic Product (GDP) per capita, and habitat richness emerged as the strongest drivers of human hantavirus disease risk, with non-linear effects varying across regions. Notably, habitat richness, as a proxy for biodiversity, exhibited a strong non-linear relationship with disease risk. Increasing habitat richness was first associated with higher disease risk at intermediate levels, whereas further increases tended to significantly reduce risk. Our results demonstrated that the occurrence of human hantavirus infection in Europe is shaped by multiple cross-sector drivers, highlighting the need to adopt an integrated One Health surveillance approach that incorporates both ecological and socio-economic contexts to improve the prediction of high-risk areas and periods of increased disease transmission. In addition, it is important to emphasize the role of biodiversity in hantavirus infection, particularly habitat richness, as changes in ecosystem diversity can alter the overall risk of disease occurrence. Based on these findings, we propose a mechanistic hypothesis for major regional hantavirus outbreaks, which provides a framework for future research and evidence-based policy development.
Klebsiella (K.) pneumoniae is a major antimicrobial-resistant pathogen of global concern. It has increasingly been reported outside clinical settings, including food products. However, genomic data on food-derived K. pneumoniae in Egypt remain limited. In this study, we investigated the genomic diversity, antimicrobial susceptibility, and phylogenetic relationships of K. pneumoniae isolated from ready-for-consumption foods obtained from Egyptian supermarkets. Eleven isolates were recovered from dairy products (milk and yogurt) and catfish. Isolates were identified by MALDI-TOF MS and confirmed by whole genome sequencing (WGS). Antimicrobial susceptibility testing (AST) was performed against a panel of clinically relevant antibiotics. Genomic analyses included multilocus sequence typing (MLST), detection of resistance and virulence associated genes, and SNP based phylogenetic reconstruction. The SNP-based phylogenetic analysis was performed using an additional 77 publicly available Egyptian clinical isolates. Most isolates displayed a predominantly susceptible antimicrobial phenotype. Resistance was largely restricted to piperacillin. All genomes carried intrinsic resistance determinants, including multiple blaSHV alleles and fosA variants. These did not correlate with phenotypic resistance to cephalosporins or fosfomycin. MLST revealed heterogeneous lineages, including clinically relevant sequence types ST37 and ST105, as well as a novel sequence type. Phylogenetic analysis showed that some food-derived isolates clustered closely with the genomes of Egyptian clinical isolates. Others formed genetically distinct lineages, indicating diverse origins within the food chain. These findings show that ready-to-eat foods in Egypt can harbor genetically diverse K. pneumoniae strains. Some populations include lineages related to clinical strains, despite limited phenotypic resistance. The study highlights the importance of integrating phenotypic antimicrobial testing with WGS based surveillance. Such integration can better assess the public health significance of foodborne K. pneumoniae within a One Health framework.
