A cross-sectional study was used to identify and assess prevalence and phenotypic antimicrobial resistance (AMR) profiles of Escherichia coli and other enterobacteria isolated from healthy wildlife and livestock cohabiting at a 10,000 acres game ranch near Lusaka, Zambia. Purposive sampling was used to select wildlife and livestock based on similarities in behavior, grazing habits and close interactions with humans. Isolates (n = 66) from fecal samples collected between April and August 2018 (n = 84) were examined following modified protocols for bacteria isolation, biochemical identification, molecular detection, phylogenetic analysis, and antimicrobial susceptibility testing by disc diffusion method. Data were analyzed using R software, Genetyx ver.12 and Mega 6. Using Applied Profile Index 20E kit for biochemical identification, polymerase chain reaction assay and sequencing, sixty-six isolates were identified to species level, of which Escherichia coli (72.7%, 48/66), E. fergusonii (1.5%, 1/66), Shigella sonnei (22.7%, 14/66), Sh. flexinerri (1.5%, 1/66) and Enterobacteriaceae bacterium (1.5%, 1/66), and their relationships were illustrated in a phylogenetic tree. Phenotypic antimicrobial resistance or intermediate sensitivity expression to at least one antimicrobial agent was detected in 89.6% of the E. coli, and 73.3% of the Shigella isolates. The E. coli isolates exhibited the highest resistance rates to ampicillin (27%), ceftazidime (14.3%), cefotaxime (9.5%), and kanamycin (9.5%). Multidrug resistance (MDR) was detected in 18.8% of E. coli isolates while only 13.3% Shigella isolates showed MDR. The MDR was detected among isolates from impala and ostrich (wild animals in which no antimicrobial treatment was used), and in isolates from cattle, pigs, and goats (domesticated animals). This study indicates the possible transmission of drug-resistant microorganisms between animals cohabiting at the wildlife–livestock interface. It emphasizes the need for further investigation of the role of wildlife in the development and transmission of AMR, which is an issue of global concern.

African swine fever (ASF) is a highly contagious disease that is caused by the ASF virus (ASFV) with a high fatality rate in domestic pigs resulting in a high socio-economic impact. The pig business in Vietnam was recently affected by ASF for the first time. This study thus aimed to develop a disease dynamic model to explain how ASFV spreads in Vietnamese pig populations and suggest a protective vaccine coverage level required to prevent future outbreaks. The outbreak data were collected from ten private small-scale farms within the first wave of ASF outbreaks in Vietnam. Three methods were used to estimate the basic reproduction number (R₀), including the exponential growth method, maximum likelihood method, and attack rate method. The average R₀ values were estimated at 1.49 (95%CI: 1.05–2.21), 1.58 (95%CI: 0.92–2.56), and 1.46 (95%CI: 1.38–1.57), respectively. Based on the worst-case scenario, all pigs in a herd would be infected and removed within 50 days. We suggest vaccinating at least 80% of pigs on each farm once a commercially approved ASF vaccine is available. However, an improvement in biosecurity levels in small-scale farms is still greatly encouraged to prevent the introduction of the virus.

Porcine epidemic diarrhoea (PED) is an emerging disease in pigs that causes massive economic losses in the swine industry, with high mortality in suckling piglets. Early identification of PED virus (PEDV)-infected herd through surveillance or monitoring strategies is necessary for mass control of PED. However, a common working diagnosis system involves identifying PEDV-infected animals individually, which is a costly and time-consuming approach. Given the above information, the thrusts of this study were to develop a real-time fluorescent reverse transcription loop-mediated isothermal amplification (RtF-RT-LAMP) assay and establish a pooled testing system using faecal sample to identify PEDV-infected herd. In this study, we developed an accurate, rapid, cost-effective, and simple RtF- RT-LAMP assay for detecting the PEDV genome targeting M gene. The pooled testing system using the RtF-RT-LAMP assay was optimized such that a pool of at least 15 individual faecal samples could be analysed. The developed RtF-RT-LAMP assay in our study could support the design and implementation of large-scaled epidemiological surveys as well as active surveillance and monitoring programs for effective control of PED.

Enzootic bovine leukosis is a lethal neoplastic disease caused by bovine leukemia virus (BLV), belongs to family Retroviridae. The BLV proviral load (PVL) represents the quantity of BLV genome that has integrated into the host’s genome in BLV-infected cells. Bovine leukocyte antigen (BoLA) class II allelic polymorphisms are associated with PVLs in BLV-infected cattle. We sought to identify relationships between BoLA-DRB3 allelic heterozygosity and BLV PVLs among different cattle breeds. Blood samples from 598 BLV-infected cattle were quantified to determine their PVLs by real-time polymerase chain reaction. The results were confirmed by a BLV-enzyme-linked immunosorbent assay. Restriction fragment length polymorphism-polymerase chain reaction identified 22 BoLA-DRB3 alleles. Multivariate negative binomial regression modeling was used to test for associations between BLV PVLs and BoLA-DRB3 alleles. BoLA-DRB3.2*3, *7, *8, *11, *22, *24, and *28 alleles were significantly associated with low PVLs. BoLA-DRB3.2*10 was significantly associated with high PVLs. Some heterozygous allele combinations were associated with low PVLs (*3/*28, *7/*8, *8/*11, *10/*11, and *11/*16); others were associated with high PVLs (*1/*41, *10/*16, *10/*41, *16/*27, and *22/*27). Interestingly, the BoLA-DRB3.2*11 heterozygous allele was always strongly and independently associated with low PVLs. This is the first reported evidence of an association between heterozygous allelic combinations and BLV PVLs.

The cattle industry is suffering economic losses caused by bovine leukemia virus (BLV) and enzootic bovine leukosis (EBL), the clinical condition associated with BLV infection. This pathogen spreads easily without detection by farmers and veterinarians due to the lack of obvious clinical signs. Cattle movement strongly contributes to the inter-farm transmission of BLV. This study quantified the farm-level risk of BLV introduction using a cattle movement analysis. A generalized linear mixed model predicting the proportion of BLV-infected cattle was constructed based on weighted in-degree centrality. Our results suggest a positive association between weighted in-degree centrality and the estimated number of introduced BLV-infected cattle. Remarkably, the introduction of approximately six cattle allowed at least one BLV-infected animal to be added to the farm in the worst-case scenario. These data suggest a high risk of BLV infection on farms with a high number of cattle being introduced. Our findings indicate the need to strengthen BLV control strategies, especially along the chain of cattle movement.

B cell non-Hodgkin lymphoma is a typical extrahepatic manifestation frequently associated with hepatitis C virus (HCV) infection. The mechanism by which HCV infection leads to lymphoproliferative disorder remains unclear. Our group established HCV transgenic mice that expressed the full HCV genome in B cells (RzCD19Cre mice). We observed a 25.0% incidence of diffuse large B cell non-Hodgkin lymphomas (22.2% in male and 29.6% in female mice) within 600 days of birth. Interestingly, RzCD19Cre mice with substantially elevated serum-soluble interleukin-2 receptor α-subunit (sIL-2Rα) levels (>1000 pg/mL) developed B cell lymphomas. Another mouse model of lymphoproliferative disorder was established by persistent expression of HCV structural proteins through disruption of interferon regulatory factor-1 (irf-1^_/_/CN2 mice). Irf-1^_/_/CN2 mice showed extremely high incidences of lymphomas and lymphoproliferative disorders. Moreover, these mice showed increased levels of interleukin (IL)-2, IL-10, and Bcl-2 as well as increased Bcl-2 expression, which promoted oncogenic transformation of lymphocytes.