Spatial Distribution and Ecological Niche Modeling of Toxigenic Clostridium perfringens in Ruminants: Integrating Environmental Drivers with an ELISA-Based Toxinotyping Approach.

OBJECTIVES

Enterotoxemia, caused by Clostridium perfringens, leads to high mortality in ruminants and significant economic losses. This study aimed to toxinotype C. perfringens using the Ag-ELISA method in suspected samples from the Central Black Sea Region and surrounding provinces, while statistically and ecologically evaluating the effects of regional abiotic factors on the spread of the disease.

METHODS

Between 2021 and 2024, the Ag-ELISA test was applied to 741 intestinal content samples submitted from 11 provinces to the Samsun Veterinary Control Institute. Meteorological parameters and soil moisture index data derived from NASA satellites were utilized. Generalized Linear Mixed Models (GLMMs) based on the Negative Binomial distribution were used to determine the effects of variables, while Kernel Density Estimation (KDE) was employed to model the ecological niche distribution and case concentrations based on mean temperature and soil moisture.

RESULTS

C. perfringens and its toxins were detected in 297 (40.08%) of the samples. Toxinotyping revealed that Type A was the most prevalent strain (62.63%), followed by Type C (20.54%), Type D (13.80%), and Type B (3.03%). GLMM and KDE analyses demonstrated that soil moisture and temperature are the most influential risk factors. The KDE contour layers revealed that the cases exhibited a bimodal adaptive mechanism and specific ecological niche concentrations based on these abiotic variables.

CONCLUSIONS

C. perfringens Type A and Type C were identified as the dominant strains in the study area. Considering the bimodal adaptive mechanism and environmental niche concentrations demonstrated by KDE, selecting vaccines providing targeted protection against Types A and C is of critical importance for controlling enterotoxemia and optimizing strategic vaccination schedules in the region.