Validation and refinement of existing methods for timed mating and early pregnancy detection in guinea pigs.

Biomedical research increasingly focuses on early developmental stages to better understand homeostasis, environmental influences, and disease origins, an approach summarised by the concept of the Developmental Origins of Health and Disease. However, studying these processes in humans is challenging, highlighting the need for suitable animal models that closely mimic human pregnancy and early development. Historically, guinea pigs were the preferred model for specific research areas and are now regaining attention in embryological studies due to their physiological similarities to humans. We present an extended and standardized protocol for mating guinea pigs, building upon the methods described by Wilson et al. (2021). In this work, we verified the previously published procedures for monitoring the estrous cycle through observation of the vaginal closure membrane and for confirming pregnancy via ultrasound. In addition, we introduced new methods to improve breeding efficiency and early pregnancy assessment. Specifically, we incorporated vaginal cytology alongside vaginal membrane monitoring to increase the success rate of overnight matings. Extending on the ultrasound descriptions by Wilson et al., we provide new ultrasound-based observations of early pregnancy, including the earliest visualization of the embryonic sac at embryonic day 12 (E12) and examples of embryonic development during the first weeks of gestation. By following these step-by-step instructions, researchers new to guinea pig models can quickly establish the methodology in their laboratories, reducing the need for prolonged trial and error. This approach facilitates the broader use of guinea pigs in developmental and reproductive research, particularly due to their resemblance to humans in pregnancy, embryonic development, and parturition.

Copyright: © 2026 Mayer et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

PMID: 42013115