TopoDB: a novel multifunctional management system for laboratory animal colonies.

Adam Renschen,Adam Santaniello,Jorge R Oksenberg,Alessandro Didonna,Atsuko Matsunaga

doi:10.1093/database/baaa098

Abstract

Animal models are widely employed in basic research to test mechanistic hypotheses in a complex biological environment as well as to evaluate the therapeutic potential of candidate compounds in preclinical settings. Rodents, and in particular mice, represent the most common in vivo models for their small size, short lifespan and possibility to manipulate their genome. Over time, a typical laboratory will develop a substantial number of inbred strains and transgenic mouse lines, requiring a substantial effort, in both logistic and economic terms, to maintain an animal colony for research purposes and to safeguard the integrity of results. To meet this need, here we present TopoDB, a robust and extensible web-based platform for the rational management of laboratory animals. TopoDB allows an easy tracking of individual animals within the colony and breeding protocols as well as the convenient storage of both genetic and phenotypic data generated in the different experiments. Altogether, these features facilitate and enhance the design of in vivo research, thus reducing the number of necessary animals and the housing costs. In summary, TopoDB represents a novel valuable tool in modern biomedical research. Database URL: https://github.com/UCSF-MS-DCC/TopoDB

Highlights

Animal models are broadly employed in modern biomedical research to recapitulate specific aspects of human physiology and preclinical testing of therapeutic reagents [1]
We show the handling of clinical scores from mice after induction of experimental autoimmune encephalomyelitis (EAE), an in vivo model of multiple sclerosis (MS) that we extensively use in our research [11,12,13,14]
Using TopoDB should be a familiar experience for users of modern Internet and spreadsheet applications

Summary

Introduction

Animal models are broadly employed in modern biomedical research to recapitulate specific aspects of human physiology and preclinical testing of therapeutic reagents [1]. The possibility to structure data accessibility to multiple users allows a tighter control over the existing animal colonies, leading to improved breeding strategies and fewer animals needed for both colony maintenance and experimental purposes, in line with the principles of the 3Rs for animal research (Replacement, Reduction and Refinement) [6]. Existing solutions for managing these data vary widely Adopted tools such as paper notebooks and spreadsheets are error-prone and do not scale well to handle large data or complex colony structures. Several open-access tools have been developed over the years [7,8,9,10] Generally affordable, they often reflect the specific needs of the developers, displaying limited flexibility in different research settings. Commercial animal colony software, while generally robust and scalable, is frequently expensive and cumbersome to use, with steep learning curves that discourage their use in standard research environments

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