Metagenomic Insights into the Diverse Antibiotic Resistome of Non-Migratory Corvidae Species on the Qinghai-Tibetan Plateau

Abstract

Antibiotic resistance represents a global health crisis with far-reaching implications, impacting multiple domains concurrently, including human health, animal health, and the natural environment. Wild birds were identified as carriers and disseminators of antibiotic-resistant bacteria (ARB) and their associated antibiotic resistance genes (ARGs). A majority of studies in this area have concentrated on migratory birds as carriers for the spread of antibiotic resistance over long distances. However, there has been scant research on the resistome of non-migratory Corvidae species that heavily overlap with human activities, which limits our understanding of antibiotic resistance in these birds and hinders the development of effective management strategies. This study employed a metagenomics approach to examine the characteristics of ARGs and mobile genetic elements (MGEs) in five common Corvidae species inhabiting the Qinghai-Tibetan Plateau. The ARGs were classified into 20 major types and 567 subtypes. Notably, ARGs associated with multidrug resistance, including to macrolide-lincosamide-streptogramins, tetracyclines, beta-lactam, and bacitracin, were particularly abundant, with the subtypes acrB, bacA, macB, class C beta-lactamase, and tetA being especially prevalent. A total of 5 types of MGEs (166 subtypes) were identified across five groups of crows, and transposase genes, which indicated the presence of transposons, were identified as the most abundant type of MGEs. Moreover, some common opportunistic pathogens were identified as potential hosts for these ARGs and MGEs. Procrustes analysis and co-occurrence network analysis showed that the composition of the gut microbiota shaped the ARGs and MGEs, indicating a substantial association between these factors. The primary resistance mechanisms of ARGs in crows were identified as multidrug efflux pumps, alteration of antibiotic targets, and enzymatic inactivation. High-risk ARGs which were found to potentially pose significant risks to public health were also analyzed and resulted in the identification of 81 Rank I and 47 Rank II ARGs. Overall, our study offers a comprehensive characterization of the resistome in wild Corvidae species, enhancing our understanding of the potential public health risks associated with these birds.

Keywords: antibiotic resistance genes; avian microbiome; corvidae; gut microbiota; metagenomic sequencing.

Figure 1

Bird sampling site map.

Figure 2

ARGs detected in five crow groups. (A) Combined statistical map of ARG types and subtypes for each group. (B) Comparison of the number of ARG subtypes across five groups. Statistically significant differences among groups are indicated by different lowercase letters. (C) Heatmap of ARG type abundances per group. Statistically significant differences are indicated as follows: ns, p > 0.05; * p < 0.05; ** p < 0.01; *** p < 0.001. (D) Heatmap of ARG subtype abundances per group. (E) Upset plot illustrating shared ARG subtypes across groups. (F) Principal component analysis plots based on Bray–Curtis distances for ARG subtypes.

Figure 3

MGEs detected in five crow groups. (A) Combined statistical map of MGE types and subtypes for each group. (B) Comparison of the number of MGE subtypes across five groups. Statistically significant differences among groups are indicated by different lowercase letters. (C) Heatmap of MGE type abundances per group. Statistically significant differences are indicated as follows: ns, p > 0.05; * p < 0.05; ** p < 0.01. (D) Heatmap of MGE subtype abundances per group. (E) Venn plot illustrating shared MGE subtypes across groups. (F) Principal component analysis plots based on Bray–Curtis distances for MGE subtypes.

Figure 4

Composition of microbial communities in five crow groups. Taxonomic analyses conducted at the levels of (A) phylum and (B) genus.

Figure 5

Interrelationships among gut microbes, ARGs, and MGEs. The correlations are shown between (A) ARGs and MGEs, (B) ARGs and gut microbes, and (C) gut microbes and MGEs. Procrustes analyses demonstrate the relationships between (D) ARGs and gut microbes, (E) ARGs and MGEs, and (F) gut microbes and MGEs.

Figure 6

Network analysis showing the co-occurrence relationships among ARGs, MGEs, and gut microbes (at the genus level).

Figure 7

Hosts of the resistome. ARG hosts at the phylum (A) and genus (B) levels. MGE hosts at the phylum (C) and genus (D) levels. The inner circle indicates the annotation of phylum and genus hosts, while the outer circle represents the composition of ARG and MGE types.

Figure 8

Resistance mechanisms in five crow groups. (A) Diversity of resistance mechanisms in each group. (B) Relative abundance composition of resistance mechanisms across groups. (C) Comparison of the top two resistance mechanisms abundances among groups.

Figure 9

High-risk ARGs in five crow groups. (A) Comparison of inter-group differences in the relative abundance of high-risk ARGs at the rank I and rank II level. (B) Heatmap showing the abundances of rank I high-risk ARGs across groups. (C) Heatmap showing the abundances of rank II high-risk ARGs across groups.