Microbial food spoilage is responsible for a considerable amount of waste and can cause food-borne diseases in humans, particularly in immunocompromised individuals and children. Therefore, preventing microbial food spoilage is a major concern for health authorities, regulators, consumers, and the food industry. However, the contamination of food products is difficult to control because there are several potential sources during production, processing, storage, distribution, and consumption, where microorganisms come in contact with the product. Here, we use high-throughput full-length 16S rRNA gene sequencing to provide insights into bacterial community structure throughout a pork-processing plant. Specifically, we investigated what proportion of bacteria on meat are presumptively not animal-associated and are therefore transferred during cutting via personnel, equipment, machines, or the slaughter environment. We then created a facility-specific transmission map of bacterial flow, which predicted previously unknown sources of bacterial contamination. This allowed us to pinpoint specific taxa to particular environmental sources and provide the facility with essential information for targeted disinfection. For example, Moraxella spp., a prominent meat spoilage organism, which was one of the most abundant amplicon sequence variants (ASVs) detected on the meat, was most likely transferred from the gloves of employees, a railing at the classification step, and the polishing tunnel whips. Our results suggest that high-throughput full-length 16S rRNA gene sequencing has great potential in food monitoring applications.
Multiple enteropathogens such as bovine rotavirus (BRV), bovine coronavirus (BCoV), Escherichia coli K99 (ETEC) and Cryptosporidium spp. (Crypto) are the most common causes of calf diarrhoea during the first 30 days of animal age. Three weighted-stratified random-effects meta-analyses were performed to calculate the worldwide prevalence of mixed infections of the causative agents (i.e., BRV-BCoV, BRV-ETEC, BRV-Crypto) and their potential influencing factors. The meta-analysis covered 41 studies (94 sub-studies) in 21 countries that determined the presence or absence of mixed infections in global calf populations. The highest worldwide estimated pooled prevalence was identified for BRV-Crypto (6.69%), followed by BRV-BCoV (2.84%), and BRV-ETEC (1.64%). The chance of detecting BCoV in calves with diarrhoea was 1.83 higher in the presence of BRV compared to calves without BRV, whereby an inhibition effect (odds ratio: 0.77) was determined between BRV and Crypto infections. The diagnostic methods were identified as a significant influencing factor in the detection of all considered mixed infections, while the other analysed factors differed in relation to their effect on prevalence. In contrast to BRV-BCoV, the prevalence of BRV-ETEC and BRV-Crypto mixed infections followed the course of individual ETEC and Crypto prevalence related to the age class of the sampled animals.
The COST action “Standardising output-based surveillance to control non-regulated diseases of cattle in the European Union (SOUND control),” aims to harmonise the results of surveillance and control programmes (CPs) for non-EU regulated cattle diseases to facilitate safe trade and improve overall control of cattle infectious diseases. In this paper we aimed to provide an overview on the diversity of control for these diseases in Europe. A non-EU regulated cattle disease was defined as an infectious disease of cattle with no or limited control at EU level, which is not included in the European Union Animal health law Categories A or B under Commission Implementing Regulation (EU) 2020/2002. A CP was defined as surveillance and/or intervention strategies designed to lower the incidence, prevalence, mortality or prove freedom from a specific disease in a region or country. Passive surveillance, and active surveillance of breeding bulls under Council Directive 88/407/EEC were not considered as CPs. A questionnaire was designed to obtain country-specific information about CPs for each disease. Animal health experts from 33 European countries completed the questionnaire. Overall, there are 23 diseases for which a CP exists in one or more of the countries studied. The diseases for which CPs exist in the highest number of countries are enzootic bovine leukosis, bluetongue, infectious bovine rhinotracheitis, bovine viral diarrhoea and anthrax (CPs reported by between 16 and 31 countries). Every participating country has on average, 6 CPs (min–max: 1–13) in place. Most programmes are implemented at a national level (86%) and are applied to both dairy and non-dairy cattle (75%). Approximately one-third of the CPs are voluntary, and the funding structure is divided between government and private resources. Countries that have eradicated diseases like enzootic bovine leukosis, bluetongue, infectious bovine rhinotracheitis and bovine viral diarrhoea have implemented CPs for other diseases to further improve the health status of cattle in their country. The control of non-EU regulated cattle diseases is very heterogenous in Europe. Therefore, the standardising of the outputs of these programmes to enable comparison represents a challenge.
The impact of subacute rumen acidosis (SARA) on the rumen bacterial community has been frequently studied in in vivo trials. Here we investigated whether these alterations can be mirrored by using the rumen simulation technique (RUSITEC) as an in vitro model for this disease. We hypothezised that the bacterial community fully recovers after a subacute ruminal acidosis challenge. We combined a PacBio nearly full-length 16S rRNA gene analysis with 16S rRNA gene Illumina MiSeq sequencing of the V4 hypervariable region. With this hybrid approach, we aimed to get an increased taxonomic resolution of the most abundant bacterial groups and an overview of the total bacterial diversity. The experiment consisted of a control period I and a SARA challenge and ended after a control period II, of which each period lasted 5 d. Subacute acidosis was induced by applying two buffer solutions, which were reduced in their buffering capacity (SARA buffers) during the SARA challenge. Two control groups were constantly infused with the standard buffer solution. Furthermore, the two SARA buffers were combined with three different feeding variations, which differed in their concentrateto-hay ratio. The induction of SARA led to a decrease in pH below 5.8, which then turned into a steady-state SARA. Decreasing pH values led to a reduction in bacterial diversity and richness. Moreover, the diversity of solid-associated bacteria was lower for high concentrate groups throughout all experimental periods. Generally, Firmicutes and Bacteroidetes were the predominant phyla in the solid and the liquid phase. During the SARA period, we observed a decrease in fibrolytic bacteria although lactate-producing and-utilizing families increased in certain treatment groups. The genera Lactobacillus and Prevotella dominated during the SARA period. With induction of the second control period, most bacterial groups regained their initial abundance. In conclusion, this in vitro model displayed typical bacterial alterations related to SARA and is capable of recovery from bouts of SARA. Therefore, this model can be used to mimic SARA under laboratory conditions and may contribute to a reduction in animal experiments.
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