Development and application of classical swine fever virus monoclonal antibodies derived from single B cells.

Vaccination with E2 subunit vaccines is currently the main measure to control classical swine fever virus (CSFV), which is an endemic disease, and detection of antibodies against CSFV E2 is the most effective way to evaluate herd immunity. In the present study, the E2 protein was expressed by a baculovirus expression system, and two monoclonal antibodies (mAbs), namely, 3A9 and 4F7, were successfully produced using techniques for the isolation of single B cells from splenocytes from mice immunized with the E2 protein. Moreover, two linear B-cell epitopes, 25GLTTTWKEYSHDLQL39 and 259GNTTVKVHASDERGP273, reactive to 3A9 and 4F7, respectively, were identified using epitope mapping of the E2 protein. In addition, the diagnostic performance of the two mAbs was evaluated using blocking enzyme-linked immunosorbent assay (bELISA), and the results showed that the two mAbs had high diagnostic specificity (96.08%, 94.38%) and diagnostic sensitivity (97.49%, 95.97%). Together, these findings identify two ideal candidate peptides and matching mAbs for a new method of CSFV diagnosis, which will contribute to the control and eradication of classical swine fever.

Effects of soil data and simulation unit resolution on quantifying changes of soil organic carbon at regional scale with a biogeochemical process model.

Soil organic carbon (SOC) models were often applied to regions with high heterogeneity, but limited spatially differentiated soil information and simulation unit resolution. This study, carried out in the Tai-Lake region of China, defined the uncertainty derived from application of the DeNitrification-DeComposition (DNDC) biogeochemical model in an area with heterogeneous soil properties and different simulation units. Three different resolution soil attribute databases, a polygonal capture of mapping units at 1:50,000 (P5), a county-based database of 1:50,000 (C5) and county-based database of 1:14,000,000 (C14), were used as inputs for regional DNDC simulation. The P5 and C5 databases were combined with the 1:50,000 digital soil map, which is the most detailed soil database for the Tai-Lake region. The C14 database was combined with 1:14,000,000 digital soil map, which is a coarse database and is often used for modeling at a national or regional scale in China. The soil polygons of P5 database and county boundaries of C5 and C14 databases were used as basic simulation units. Results project that from 1982 to 2000, total SOC change in the top layer (0-30 cm) of the 2.3 M ha of paddy soil in the Tai-Lake region was +1.48 Tg C, -3.99 Tg C and -15.38 Tg C based on P5, C5 and C14 databases, respectively. With the total SOC change as modeled with P5 inputs as the baseline, which is the advantages of using detailed, polygon-based soil dataset, the relative deviation of C5 and C14 were 368% and 1126%, respectively. The comparison illustrates that DNDC simulation is strongly influenced by choice of fundamental geographic resolution as well as input soil attribute detail. The results also indicate that improving the framework of DNDC is essential in creating accurate models of the soil carbon cycle.