Animal Breed Composition Is Associated With the Hindgut Microbiota Structure and β-Lactam Resistance in the Multibreed Angus-Brahman Herd

Abstract

Antibiotics have been widely used in livestock to treat and prevent bacterial diseases. However, use of antibiotics has led to the emergence of antibiotic resistant microorganisms (ARMs) in food animals. Due to the decreased efficacy of antibiotics, alternatives to antibiotics that can reduce infectious diseases in food animals to enhance animal health and growth performance are urgently required. Here, we show that animal genetics is associated with the hindgut microbiome, which is related to fat deposition and beta-lactam resistance in the gastrointestinal tract. We investigated the hindgut microbiota structure in 95 postweaning heifers belonging to the unique multibreed Angus-Brahman herd with breed composition ranging from 100% Angus to 100% Brahman. The hindgut microbial composition of postweaning heifers differed among breed groups. The mucin-degrading bacterium Akkermansia known for promoting energy expenditure was enriched in Brahman calves that contained less intramuscular fat content, while butyrate-producing bacterium Faecalibacterium was linearly positively correlated with Angus proportion. Moreover, the higher relative abundance of beta-lactam resistant genes including ampC gene and arcA gene was associated with the greater Brahman proportion. As the first study aimed at understanding changes in hindgut microbiota among beef cattle with linear gradient of breed composition and its association with marbling in meat, our results suggest that the effects of animal genetics on the gut microbiota structure is associated with fat deposition and potentially a factor affecting the gut antimicrobial resistance.

Prevalence and Molecular Characteristics of Extended-Spectrum and AmpC β-Lactamase Producing Escherichia coli in Grazing Beef Cattle

“…In addition to antibiotic usage, the selection pressure during the process of evolution in microbial communities could be another reason for naturally occurring antibiotic resistant bacteria. Recent studies suggested that genomic breed composition of cattle was also associated with different gut microbiota structure (Fan et al, 2019a) that affects the colonization of antibiotic resistant bacteria (Fan et al, 2019b). In these cases, the prevalence of antibiotic resistant bacteria might not be directly correlated with antibiotic usage, and even farms without antibiotic supplementation contained ESBL and AmpC producing bacteria in both environmental and fecal samples (Mir et al, 2016(Mir et al, , 2018Teng et al, 2019), coinciding with the results of our study (Figures 1B,D).…”

Clinically Relevant Extended-Spectrum β-Lactamase–Producing Escherichia coli Isolates From Food Animals in South Korea

“…Most of each phylogroup to which they belonged was allocated to a distinct cluster, whereas there was no difference between animal species allocations (Figure 2), suggesting that the phylogenetic relationships among the ESBL-EC STs may be closely related to their phylogroups regardless of the host animal species. Notably, the different breed composition of cattle has been reported to be associated with gut microbiota structure and β-lactam resistance (Fan et al, 2019), suggesting the impact of animal genetics on the antimicrobial-resistant bacteria profile even within the same species. We further detected various clonal STs in these isolates FIGURE 2 | Phylogenetic tree of cefotaxime-resistant Escherichia coli isolates from chickens, pigs, and cattle.…”

Predictive ability of host genetics and rumen microbiome for subclinical ketosis

“…Thresholds for OTU incidence are somewhat arbitrary, selected across literature, ranging from 5 to 80% (Benson et al, 2010;Rothschild et al, 2018). Most commonly a threshold of 50% is employed, as presence versus absence can be seen as a binary trait, and a 50% threshold is the point at which the variance of binary traits is maximized (Goodrich et al, 2014;Difford et al, 2018;Fan et al, 2019). Bacterial and archaeal OTU are then natural log-transformed after the addition of a small constant 0.01 (1% of the lowest possible count 1), which is then centered and scaled; n is the number of bacterial and archaeal OTU.…”