Meta-transcriptomic analysis of companion animal infectomes reveals their diversity and potential roles in animal and human disease

Abstract

Companion animals such as cats and dogs harbor diverse microbial communities that can potentially impact human health due to close and frequent contact. To better characterize their total infectomes and assess zoonotic risks, we characterized the overall infectomes of companion animals (cats and dogs) and evaluated their potential zoonotic risks. Meta-transcriptomic analyses were performed on 239 samples from cats and dogs collected across China, identifying 24 viral species, 270 bacterial genera, and two fungal genera. Differences in the overall microbiome and infectome composition were compared across different animal species (cats or dogs), sampling sites (rectal or oropharyngeal), and health status (healthy or diseased). Diversity analyses revealed that viral abundance was generally higher in diseased animals compared to healthy ones, while differences in microbial composition were mainly driven by sampling site, followed by animal species and health status. Disease association analyses validated the pathogenicity of known pathogens and suggested potential pathogenic roles of previously undescribed bacteria and newly discovered viruses. Cross-species transmission analyses identified seven pathogens shared between cats and dogs, such as alphacoronavirus 1, which was detected in both oropharyngeal and rectal swabs albeit with differential pathogenicity. Further analyses showed that some viruses, like alphacoronavirus 1, harbored multiple lineages exhibiting distinct pathogenicity, tissue, or host preferences. Ultimately, a systematic evolutionary screening identified 27 potential zoonotic pathogens in this sample set, with far more bacterial than viral species, implying potential health threats to humans. Overall, our meta-transcriptomic analysis reveals a landscape of actively transcribing microorganisms in major companion animals, highlighting key pathogens, those with the potential for cross-species transmission, and possible zoonotic threats.

Importance: This study provides a comprehensive characterization of the entire community of infectious microbes (viruses, bacteria, and fungi) in companion animals like cats and dogs, termed the "infectome." By analyzing hundreds of samples from across China, the researchers identified numerous known and novel pathogens, including 27 potential zoonotic agents that could pose health risks to both animals and humans. Notably, some of these zoonotic pathogens were detected even in apparently healthy pets, highlighting the importance of surveillance. The study also revealed key microbial factors associated with respiratory and gastrointestinal diseases in pets, as well as potential cross-species transmission events between cats and dogs. Overall, this work sheds light on the complex microbial landscapes of companion animals and their potential impacts on animal and human health, underscoring the need for monitoring and management of these infectious agents.

Keywords: metagenomics; microbiome; veterinary medicine; virome; zoonoses.

Fig 1

Sample overview. (a) Geographical distribution within China of the companion animal samples collected and the sample size at each location. Open-access map data were obtained at https://doi.org/10.5281/zenodo.4167299. (b) Sample types and corresponding sample sizes.

Fig 2

Overview of the infectomes of cats and dogs. (a) Heatmaps illustrating the microbial abundance in each individual sample. The abundance of viruses is quantified at the species level, while bacterial and fungal abundance are quantified at a genus-level resolution. For clarity, bacterial genera with <40 positive samples were omitted from the visual representation. (b) The abundance and diversity of viruses, bacteria and fungi in each library. The diversity of viruses was quantified by species richness (i.e., the number of viral species per sample), while the diversity of bacteria and fungi was quantified by the number of genera.

Fig 3

Comparisons of alpha and beta diversity among species, sample types, and health conditions. (a, b) Comparison of bacterial richness (a; number of bacterial genera per sample) and viral richness (b; number of viral species per sample) among sample types (anal/throat swabs), species (cats/dogs), and health conditions (healthy/diseased). (c, d) Comparison of bacterial genera compositions (c) and viral species compositions (d) among samples. P values from PERMANOVA tests are shown at the top. For all samples, we only tested the effect of sample type. For specific sample types, we tested the effect of species, health condition, and their interaction. Significant results are shown in bold black fonts.

Fig 4

Differences in prevalence in viral species among healthy and diseased animals. The prevalence of viral species detected in specific samples, sorted by prevalence in diseased animals (red) and then by prevalence in healthy animals (blue).

Fig 5

Differential abundance analysis (DAA) of the infectomes of healthy and diseased animals. (a−d) Heatmaps demonstrating the abundance differences of microbial taxa (bacterial and fungal genera; viral species) among diseased and healthy animals. DAAs were performed using three methods—LEfSe, DESeq2, and Wilcoxon tests. The bar plots on the left exhibit the log-transformed fold change in abundance (RPM) of the corresponding taxa.

Fig 6

Maximum likelihood phylogenetic trees of six viral pathogens. The phylogenies were inferred using key functional genes (nucleotide sequences): Alphacoronavirus 1 (S gene), Feline calicivirus (capsid gene), Carnivore protoparvovirus 1 (VP1 gene), Nowalkvirus (ORF2 gene), Canine vesivirus (capsid gene), and Canine distemper virus (H gene). Host species and tissue type are indicated. The trees are midpoint rooted for clarity, with branch lengths reflecting the number of substitutions per site.

Fig 7

The virus-sharing network between cats and dogs. Nodes represent either viral species or specific sample types (rectal/throat swabs of cats/dogs). Lines between nodes indicate the presence of a specific viral species in corresponding samples, and the line width is proportional to the number of positive samples.