Search bioRxiv⌕ Search

Biology subjects

Norimine, J.

Publications and source records attributed to Norimine, J..

2 recordsLinked to original sources

Identifying Pathogen and Allele Type Simultaneously (IPATS) in a single well using droplet digital PCR

A combined host biomarker and pathogen diagnosis provides insight into disease progression risk and contributes to appropriate clinical decision-making regarding prevention and treatment. In preventive veterinary medicine, such combined diagnosis could improve risk-based livestock herd management. We developed a single-well based test for combined diagnosis of bovine leukemia virus (BLV) and bovine MHC (BoLA)-DRB3 alleles. A fourplex droplet digital PCR method targeting the BLV pol gene, BLV-susceptible DRB3*016:01 allele, resistant DRB3*009:02 allele, and housekeeping RPP30 gene (IPATS-BLV) successfully measured the percentage of BLV-infected cells and determined allele types precisely. Furthermore, it discriminated homozygous from heterozygous carriers. Using this method to determine the impact of carrying these alleles on the BLV proviral load (PVL), we found DRB3*009:02-carrying cattle could suppress the PVL to a low or undetectable level, even with the presence of a susceptible allele. Although the population of DRB3*016:01-carrying cattle showed significantly higher PVLs when compared with cattle carrying other alleles, their individual PVLs were highly variable. Because of the simplicity and speed of this single-well assay, IPATS could be a suitable platform for the combined diagnosis of host biomarkers and pathogens in a wide range of other systems.

microbiology↗

Identification of meteorological factors affecting migration of wild birds into miyazaki and its relation to circulation of highly pathogenic avian influenza virus

Aim of our study is to establish models for predicting the number of migratory wild birds based on the meteorological data. From 136 species of wild birds, which have been observed at Futatsudate in Miyazaki, Japan, from 2008 to 2016, we selected the potential high-risk species, which can introduce highly pathogenic avian influenza (HPAI) virus into Miyazaki; we defined them as \"risky birds\". We then performed regression analysis to model the relationship between the number of risky birds and meteorological data. We selected 10 wild bird species as risky birds: Mallard (Anas platyrhynchos), Northern pintail (Anas acuta), Eurasian wigeon (Anas penelope), Eurasian teal (Anas crecca), Common pochard (Aythya ferina), Eurasian coot (Fulica atra), Northern shoveler (Anas clypeata), Common shelduck (Tadorna tadorna), Tufted duck (Aythya fuligula), and Herring gull (Larus argentatus). We succeeded in identifying five meteorological factors associated with their migration: station pressure, mean value of global solar radiation, minimum of daily maximum temperature, days with thundering, and days with daily hours of daylight under 0.1 h. We could establish some models for predicting the number of risky birds based only on the published meteorological data, without manual counting. Dynamics of migratory wild birds has relevance to the risk of HPAI outbreak, so our data could contribute to save the cost and time in strengthening preventive measures against the epidemics.

epidemiology↗