Background: Antibiotic-resistant pathogens pose high risks to human and animal health worldwide. In recent years, the role of gut microbiota as a reservoir of antibiotic resistance genes (ARGs) in humans and animals has been increasingly investigated. However, the structure and function of the gut bacterial community, as well as the ARGs they carry in migratory birds remain unknown. Results: Here, we collected samples from migratory bird species and their associated environments and characterized their gut microbiomes and resistomes using shotgun metagenomic sequencing. We found that migratory birds vary greatly in gut bacterial composition but are similar in their microbiome metabolism and function. Birds from the same environment tend to harbor similar bacterial communities. In total, 1030 different ARGs (202 resistance types) conferring resistance to tetracycline, aminoglycoside, β-lactam, sulphonamide, chloramphenicol, macrolide-lincosamide-streptogramin (MLS), and quinolone are identified. Procrustes analysis indicated that microbial community structure is not correlated with the resistome in migratory birds. Moreover, metagenomic assembly-based host tracking revealed that most of the ARG-carrying contigs originate from Proteobacteria. Co-occurrence patterns revealed by network analysis showed that emrD, emrY, ANT(6)-Ia, and tetO, the hubs of ARG type network, are indicators of other co-occurring ARG types. Compared with the microbiomes and resistomes in the environment, migratory birds harbor a lower phylogenetic diversity but have more antibiotic resistance proteins. Interestingly, we found that the mcr-1 resistance gene is widespread among different birds, accounting for 50% of the total samples. Meanwhile, a large number of novel β-lactamase genes are also reconstructed from bird metagenomic assemblies based on fARGene software. Conclusions: Our study provides a comprehensive overview of the diversity and abundance of ARGs in migratory birds and highlights the possible role of migratory birds as ARG disseminators into the environment.

In contrast with the stability effects of trapped energetic ions on tearing modes, the effects of circulating energetic ions (CEI) on tearing modes depend on the toroidal circulating direction, and are closely related to the momentum of energetic ions. CEI provide an additional source or sink of momentum to affect tearing modes. For co-CEI, tearing modes can be stabilized if the momentum of energetic ions is large enough. On the other hand, the growth of tearing modes can be enhanced by counter-CEI. Further, a possibility to suppress the island growth of neoclassical tearing modes by co-CEI is pointed out.

The bar-headed goose is currently one of the most popular species for rare birds breeding in China. However, bar-headed geese in captivity display a reduced reproductive rate. The gut microbiome has been shown to influence host factors such as nutrient and energy metabolism, immune homeostasis and reproduction. It is therefore of great scientific and agriculture value to analyze the microbial communities associated with bar-headed geese in order to improve their reproductive rate. Here we describe the first comparative study of the gut microbial communities of bar-headed geese in three different breeding pattern groups by 16SrRNA sequences using the Illumina MiSeq platform. The results showed that Firmicutes predominated (58.33%) among wild bar-headed geese followed by Proteobacteria (30.67%), Actinobacteria (7.33%) and Bacteroidetes (3.33%). In semi-artificial breeding group, Firmicutes was also the most abundant bacteria (62.00%), followed by Bacteroidetes (28.67%), Proteobacteria (4.20%), Actinobacteria (3.27%) and Fusobacteria (1.51%). The microbial communities of artificial breeding group were dominated by Firmicutes (60.67%), Fusobacteria (29.67%) and Proteobacteria (9.33%). Wild bar-headed geese had a significant higher relative abundance of Proteobacteria and Actinobacteria, while semi-artificial breeding bar-headed geese had significantly more Bacteroidetes. The semi-artificial breeding group had the highest microbial community diversity and richness, followed by wild group, and then the artificial breeding group. The marked differences of genus level group-specific microbes create a baseline for future bar-headed goose microbiology research.