The study of host microbe interactions is hampered by the complexity and inter-individual variability of the human gut microbiota. Therefore, a simplified human intestinal microbiota (SIHUMI) consisting of seven bacterial species was introduced into germfree rats. Species selection was based on numerical importance and fermentative abilities in the human gut. Association of the rats with the SIHUMI (Anaerostipes caccae, Bacteroides thetaiotaomicron, Bifidobacterium longum, Blautia producta, Clostridium ramosum, Escherichia coli and Lactobacillus plantarum) resulted in increased faecal concentrations of short chain fatty acids compared to germfree animals. Since the faecal butyrate concentration was low (0.9 ± 0.5 µmol/g dry matter) the SIHUMI was complemented with Clostridium butyricum. This extended bacterial community (SIHUMIx) led to an increased faecal butyrate concentration of 1.5 ± 0.7 µmol/g dry matter. Besides forming SCFA, the SIHUMIx was capable of degrading mucins, β-aspartylglycine and bilirubin. These features are characteristic of conventional animals but not observed in germfree animals. Dietary interventions with modifications in fibre and fat content led to changes in the proportion of community members. The relative increase of one member of this community in response to a high-fat diet reflects the situation reported for obese mice and human subjects. The strength of the model communities is their remarkable stability over time and their easy transfer to the offspring.

BackgroundDiets high in cereal-fiber (HCF) have been shown to improve whole-body insulin sensitivity. In search for potential mechanisms we hypothesized that a supplemented HCF-diet influences the composition of the human gut microbiota and/or biomarkers of colonic carbohydrate fermentation.MethodsWe performed a randomized controlled 18-week intervention in group-matched overweight participants. Fecal samples of 69 participants receiving isoenergetic HCF (cereal-fiber 43 g/day), or control (cereal-fiber 14 g/day), or high-protein (HP, 28% of energy-intake, cereal-fiber 14 g/day), or moderately high cereal fiber/protein diets (MIX; protein 23% of energy-intake, cereal-fiber 26 g/day) with comparable fat contents were investigated for diet-induced changes of dominant groups of the gut microbiota, and of fecal short-chain fatty-acids (SCFA) including several of their proposed targets, after 0, 6, and 18-weeks of dietary intervention. In vitro fermentation of the cereal fiber extracts as used in the HCF and MIX diets was analyzed using gas chromatography. Diet-induced effects on whole-body insulin-sensitivity were measured using euglycaemic-hyperinsulinemic clamps and re-calculated in the here investigated subset of n = 69 participants that provided sufficient fecal samples on all study days.ResultsGut microbiota groups and biomarkers of colonic fermentation were comparable between groups at baseline (week 0). No diet-induced differences were detected between groups during this isoenergetic intervention, neither in the full model nor in uncorrected subgroup-analyses. The cereal-fiber extract as used for preparation of the supplements in the HCF and MIX groups did not support in vitro fermentation. Fecal acetate, propionate, and butyrate concentrations remained unchanged, as well as potential targets of increased SCFA, whereas valerate increased after 6-weeks in the HP-group only (p = 0.037). Insulin-sensitivity significantly increased in the HCF-group from week-6 (baseline M-value 3.8 ± 0.4 vs 4.3 ± 0.4 mg·kg-1·min-1, p = 0.015; full model 0-18-weeks, treatment-x-time interaction, p = 0.046).ConclusionsChanges in the composition of the gut microbiota and/or markers of colonic carbohydrate fermentation did not contribute explaining the observed early onset and significant improvement of whole-body insulin sensitivity with the here investigated HCF-diet.Trial registrationThis trial was registered at http://www.clinicaltrials.gov as NCT00579657

Objectives: Invasive listeriosis is a severe foodborne infection caused by Listeria (L.) monocytogenes. The aim of this investigation was to verify and describe a molecular cluster of listeriosis patients and identify factors leading to this outbreak. Methods: Whole genome sequencing and core genome multilocus sequence typing were used for subtyping L. monocytogenes isolates from listeriosis cases and food samples in Germany. Patient interviews and investigational tracing of foodstuffs offered in health-care facilities (HCF), where some of the cases occurred, were conducted. Results: We identified a German-wide listeriosis outbreak with 39 genetically related cases occurring between 2014 and 2019. Three patients died as a result of listeriosis. After identification of HCF in different regions of Germany for at least 13 cases as places of exposure, investigational tracing of food supplies in six prioritized HCF revealed meat products from one company (X) as a commonality. Subsequently the outbreak strain was analysed in six isolates from ready-to-eat meat products and one isolate from the production environment of company X. No further Sigma1 cases were detected after recall of the meat products from the market and closure of company X (as of August 2020). Conclusions: Interdisciplinary efforts including whole genome sequencing, epidemiological investigations in patients and investigational tracing of foods were essential to identify the source of infections, and thereby prevent further illnesses and deaths. This outbreak underlines the vulnerability of hospitalized patients for foodborne diseases, such as listeriosis. Food producers and HCF should minimize the risk of microbiological hazards when producing, selecting and preparing food for patients.

Despite extensive monitoring programs and preventative measures, Salmonella spp. continue to cause tens of thousands human infections per year, as well as many regional and international food-borne outbreaks, that are of great importance for public health and cause significant socio-economic costs. In Germany, salmonellosis is the second most common cause of bacterial diarrhea in humans and is associated with high hospitalization rates. Whole-genome sequencing (WGS) combined with data analysis is a high throughput technology with an unprecedented discriminatory power, which is particularly well suited for targeted pathogen monitoring, rapid cluster detection and assignment of possible infection sources. However, an effective implementation of WGS methods for large-scale microbial pathogen detection and surveillance has been hampered by the lack of standardized methods, uniform quality criteria and strategies for data sharing, all of which are essential for a successful interpretation of sequencing data from different sources. To overcome these challenges, the national GenoSalmSurv project aims to establish a working model for an integrated genome-based surveillance system of Salmonella spp. in Germany, based on a decentralized data analysis. Backbone of the model is the harmonization of laboratory procedures and sequencing protocols, the implementation of open-source bioinformatics tools for data analysis at each institution and the establishment of routine practices for cross-sectoral data sharing for a uniform result interpretation. With this model, we present a working solution for cross-sector interpretation of sequencing data from different sources (such as human, veterinarian, food, feed and environmental) and outline how a decentralized data analysis can contribute to a uniform cluster detection and facilitate outbreak investigations.

In spring 2016, Greece reported an outbreak caused by a previously undescribed Salmonella enterica subsp. enterica serotype (antigenic formula 11:z41:e,n,z15) via the Epidemic Intelligence Information System for Food- and Waterborne Diseases and Zoonoses (EPIS-FWD), with epidemiological evidence for sesame products as presumptive vehicle. Subsequently, Germany, Czech Republic, Luxembourg and the United Kingdom (UK) reported infections with this novel serotype via EPIS-FWD. Concerned countries in collaboration with the European Centre for Disease Prevention and Control (ECDC) and European Food Safety Authority (EFSA) adopted a common outbreak case definition. An outbreak case was defined as a laboratory-confirmed notification of the novel Salmonella serotype. Between March 2016 and April 2017, 47 outbreak cases were notified (Greece: n = 22; Germany: n = 13; Czech Republic: n = 5; Luxembourg: n = 4; UK: n = 3). Whole genome sequencing revealed the very close genetic relatedness of isolates from all affected countries. Interviews focusing on sesame product consumption, suspicious food item testing and trace-back analysis following Salmonella spp. detection in food products identified a company in Greece where sesame seeds from different countries were processed. Through European collaboration, it was possible to identify and recall sesame spread as one contaminated food item serving as vehicle of infection and trace it back to its origin.