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ABSTRACT: Globally, Campylobacter spp. are prominent causative agents of food-borne gastroenteritis. These pathogens are commonly detected using conventional culture methods; however, culture methods are unable to detect viable but nonculturable (VBNC) bacteria. Currently, the detection rate of Campylobacter spp. on chicken meat does not correlate with the seasonal peak of human campylobacteriosis. We hypothesized that this may be due to the presence of undetectable VBNC Campylobacter spp. Therefore, we previously established a quantitative PCR assay using propidium monoazide (PMA-qPCR), which can detect viable Campylobacter cells. In this study, PMA-qPCR was conducted to detect viable Campylobacter spp. in chicken meat, and the detection rates of PMA-qPCR and the culture method throughout all 4 seasons were compared. A total of 105 chicken meat samples (whole legs, breast fillets, and livers) were screened for the presence of Campylobacter spp. using both PMA-qPCR and the conventional culture method. The detection rates of the 2 methods did not differ significantly; however, the positive and negative samples were not always consistent. Detection rates in March were significantly lower compared to months with the highest detection rates. These results suggest that, to increase the detection rate of Campylobacter spp., the 2 methods should be used in parallel. In this study, PMA-qPCR could not detect VBNC Campylobacter spp. effectively in C. jejuni-spiked chicken meat. Further studies using improved viability-qPCR should be performed to describe the impact of the VBNC state of Campylobacter spp. on the detection of this bacterium in chicken meat.

ABSTRACT: Enzootic bovine leukosis (EBL) is a B-cell lymphosarcoma caused by bovine leukemia virus (BLV) infection. In Japan, cattle diagnosed with EBL are not permitted for human consumption by the law, thereby causing serious economic losses to farmers. The prevalence of BLV is high in Japan (40.9% in dairy cattle and 28.7% in beef cattle, respectively), which makes it difficult to perform the test-and-slaughter of BLV-infected cattle. This necessitates preventing the spread of BLV infection in cattle by early detection, segregation, and the removal of BLV-infected cattle with high proviral load, which are considered high risk for BLV transmission. We aimed to identify cattle that were at high risk for BLV transmission by comparing microRNA (miRNA) profiles in milk small extracellular vesicles (sEV). At first, miRNA profiles in sEV were compared among 4 uninfected cattle and 4 BLV-infected cattle with high proviral load by using a microarray containing mixed probes for miRNA of cattle and humans. Significantly lower amounts of hsa-miR-557 and hsa-miR-19b-1-5p, and insignificantly but higher amounts of hsa-miR-424-5p were observed in milk sEV from BLV-infected cattle than those from uninfected cattle. Next, to evaluate the utility of the aforementioned miRNAs for the identification of cattle that were at high risk for BLV transmission, we performed quantitative real-time PCR using milk sEV newly collected from 5 uninfected cattle and 17 BLV-infected cattle with high proviral load. The cycle threshold value of hsa-miR-424-5p was significantly lower in milk sEV from BLV-infected cattle. The PCR detection was unavailable or a significant difference was not observed for hsa-miR-557 and hsa-miR-19b-1-5p, respectively. These results suggest that the amount of hsa-miR-424-5p was higher in milk sEV from BLV-infected cattle and increasing the hsa-miR-424-5p in milk sEV could be one of the characteristic trends in cattle that are high risk for BLV transmission. Moreover, assessing characteristic miRNA amounts in milk sEV, which can be recovered twice a day by milking, could be useful for the routine monitoring of cattle in dairy herds instead of blood collection.

Milk extracellular vesicles (EVs) are nanoparticles that contain proteins, mRNAs, microRNAs, DNAs, and lipids that involved in several biological functions. Milk EVs provide proteins that could represent relevant novel biomarkers for monitoring of different diseases such as breast cancer and mastitis in humans and animals, respectively. Bovine leukemia virus (BLV) is an oncogenic virus that causes progressive B-cell lymphosarcoma in cattle. Here, we aimed to identify proteins in milk EVs from BLV-infected cattle compared with those from uninfcetd cattle. Proteomic analysis was performed by using a comprehensive nano liquid chromatography-tandem mass spectrometry (nanoLC-MS/MS) approach. Identified proteins were analyzed by using a proteomic software, Scaffold-Data Independent Acquisition (Scaffold-DIA).

Appropriate control of carcass temperatures in slaughterhouses requires an accurate understanding of extrinsic and intrinsic factors present after slaughter and dressing. Therefore, we use large amounts of data required under the hazard analysis and critical control point system that are accumulated in daily business reports compiled by food business operators. This data aims to clarify the influencing factors or affectors of the chilling processes for beef and pork carcasses in a slaughterhouse using graphical modeling (GM), which is an explorative method in multivariate data analysis. GM has been widely used for statistical causality analysis in visual and flexible modeling. GM is carried out using the following parameters: outside temperature and humidity, number of carcasses in a chilling room on each operating day and during every afternoon of operation, time of sealing a chilling room, pre-set temperature in a chilling room, chilling room temperature at 16:30 on the day of slaughter and dressing and at 8:00 on the next day, and surface and core temperatures of carcasses. These parameters are set in a three-layered structure comprising (1) cause, (2) intermediate effect, and (3) effect. Covariance selection is performed to statistically eliminate spurious correlation. Path diagrams are drawn for beef and pork in GM for visualization. The data herein has contributed to the first attempt at the use of GM to statistically verify causality in the food manufacturing process. These data can be used to determine causality between carcass temperature and affectors in the chilling process via GM and thus minimize bias. Analyses of the present data are reported in the article “Chilling control of beef and pork carcasses in a slaughterhouse based on causality analysis by graphical modeling” [1].