Ozawa, R. | Search bioRxiv

bioRxiv2025

Development of a sandwich ELISA for the detection of bovine A1 beta-casein

The genetic variant A2 beta-casein is associated with fewer digestive and absorption issues compared to A1 beta-casein, leading to increased global demand for A2 milk. However, contamination with the A1 variant during collection, transportation, or sterilization of A2 milk poses a risk, necessitating a verification test to ensure A2 milk does not contain A1 beta-casein. We developed an A1-specific monoclonal antibody (mAb) and a general mAb that reacts with both A1 and A2 variants using the iliac lymph node method. A sandwich ELISA was created using the general mAb as the capture antibody and the A1-specific mAb as the detection antibody to identify A1 beta-casein in milk. This ELISA successfully detected A1 beta-casein in raw and pasteurized A2 milk, including ultra-high temperature treated milk. The test identified A1 beta-casein when the A1 spike in A2 milk exceeded 1% in volume, indicating its capability to detect contamination from one A1A1 cow in a herd of one hundred A2A2 cows. The developed A1 beta-casein ELISA is suitable for high-throughput analysis and can be valuable for monitoring A1 beta-casein contamination in commercially produced A2 milk.

zoology↗

bioRxiv2025

Contrasting ecological communities in rice paddy fields under conventional and no-fertilizer farming practices

Global crop production is essential for providing energy and nutrients to humans, but agricultural systems contribute substantially to environmental issues, making it crucial to find sustainable methods for crop production. In this study, we conducted extensive field monitoring of two rice paddy fields in Kyoto Prefecture, Japan, where a rice variety, Hinohikari, was cultivated to investigate how ecological communities influence rice growth and yields under two contrasting farming practices: conventional farming and no-fertilizer farming. We had three objectives: (1) to monitor rice growth and ecological dynamics to create a comprehensive ecological time series using quantitative environmental DNA metabarcoding and complementary monitoring methods, (2) to identify ecological variables that causally affect rice performance using nonlinear time series analysis, and (3) to examine the effects of the two farming practices on ecological variables and rice performance. As expected, the no-fertilizer paddy field showed lower rice growth and yields but still produced 40-50% of the yields of the conventional field. Ecological monitoring revealed contrasting ecological communities between the two fields, particularly among plant species on the paddy ridges and microbial taxa. Twenty-five taxa had statistically clear causal influences on rice performance. While the per-abundance influences of the causal taxa were largely similar in both paddy fields, their abundances were different, contributing to the differences in the overall effects of these taxa on the rice performance. These findings suggest that the abundance of causal taxa, along with nutrient conditions, may have driven differences in rice growth between the two paddy fields.

ecology↗