Microbiome-derived metabolic signalling for healthy weight in pets

Overview

This offering is a computational discovery program targeting microbiome-derived proteins that support healthy weight in dogs and cats. The starting point is Ruminococcus torques ATCC 27756, a human-derived strain that produces RORDEP proteins. In rodents, RORDEP improved weight-related outcomes, and in a short human study, the producing strain triggered gut-hormone responses. Because related RORDEP sequences have been found in cat samples and R. torques species are present in published dog and cat microbiome data, the research will search for better-suited pet-associated strains and proteins. The goal is to develop a canine- or feline-specific microbiome-based ingredient with metabolic benefits, backed by genomic and protein-level evidence.

Technical specifications

The project uses publicly available dog and cat microbiome resources to identify candidate bioactive proteins and the strains that encode them. Methods include:

• Sequence comparison against known RORDEP proteins and related metabolic signalling peptides
• Machine-learning protein language models, trained on protein sequences, to screen dog and cat microbiome genomes for candidate bioactivity
• Structural analysis to prioritise proteins likely to interact with host pathways
• Ranking based on biological evidence, pet association, available genomic safety information, and access to strains

The core deliverable is a documented shortlist of promising protein–producer pairs, with supporting evidence and recommended validation steps. The human-derived R. torques/RORDEP system serves as the reference proof of concept; the aim is to find strains more closely associated with dogs or cats that can be developed into ingredients for pet health applications.

Technology readiness level

The underlying proof of concept has demonstrated weight-related effects in rodents and short-term gut-hormone responses in humans, but the pet-specific intervention is at an early stage. The current three-month project focuses on computational discovery and candidate prioritisation. Follow-on validation would use DTU's cell-based, in vitro and mouse-model capabilities, beginning with protein production and relevant host responses. Dedicated pet studies and formulation work would follow candidate validation, so the solution is not yet ready for commercial use.