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Abstract Background The emergence of antimicrobial resistance is a major threat to global health and has placed pressure on the livestock industry to eliminate the use of antibiotic growth promotants (AGPs) as feed additives. To mitigate their removal, efficacious alternatives are required. AGPs are thought to operate through modulating the gut microbiome to limit opportunities for colonization by pathogens, increase nutrient utilization, and reduce inflammation. However, little is known concerning the underlying mechanisms. Previous studies investigating the effects of AGPs on the poultry gut microbiome have largely focused on 16S rDNA surveys based on a single gastrointestinal (GI) site, diet, and/or timepoint, resulting in an inconsistent view of their impact on community composition. Methods In this study, we perform a systematic investigation of both the composition and function of the chicken gut microbiome, in response to AGPs. Birds were raised under two different diets and AGP treatments, and 16S rDNA surveys applied to six GI sites sampled at three key timepoints of the poultry life cycle. Functional investigations were performed through metatranscriptomics analyses and metabolomics. Results Our study reveals a more nuanced view of the impact of AGPs, dependent on age of bird, diet, and intestinal site sampled. Although AGPs have a limited impact on taxonomic abundances, they do appear to redefine influential taxa that may promote the exclusion of other taxa. Microbiome expression profiles further reveal a complex landscape in both the expression and taxonomic representation of multiple pathways including cell wall biogenesis, antimicrobial resistance, and several involved in energy, amino acid, and nucleotide metabolism. Many AGP-induced changes in metabolic enzyme expression likely serve to redirect metabolic flux with the potential to regulate bacterial growth or produce metabolites that impact the host. Conclusions As alternative feed additives are developed to mimic the action of AGPs, our study highlights the need to ensure such alternatives result in functional changes that are consistent with site-, age-, and diet-associated taxa. The genes and pathways identified in this study are therefore expected to drive future studies, applying tools such as community-based metabolic modeling, focusing on the mechanistic impact of different dietary regimes on the microbiome. Consequently, the data generated in this study will be crucial for the development of next-generation feed additives targeting gut health and poultry production. Video Abstract

Abstract Background Few studies have examined how maternal body mass index (BMI), mode of delivery and ethnicity affect the microbial composition of human milk and none have examined associations with maternal metabolic status. Given the high prevalence of maternal adiposity and impaired glucose metabolism, we systematically investigated the associations between these maternal factors in women ≥20 years and milk microbial composition and predicted functionality by V4-16S ribosomal RNA gene sequencing (NCT01405547; https://clinicaltrials.gov/ct2/show/NCT01405547 ). Demographic data, weight, height, and a 3-h oral glucose tolerance test were gathered at 30 (95% CI: 25–33) weeks gestation, and milk samples were collected at 3 months post-partum (n = 113). Results Multivariable linear regression analyses demonstrated no significant associations between maternal characteristics (maternal BMI [pre-pregnancy, 3 months post-partum], glucose tolerance, mode of delivery and ethnicity) and milk microbiota alpha-diversity; however, pre-pregnancy BMI was associated with human milk microbiota beta-diversity (Bray-Curtis R2 = 0.037). Women with a pre-pregnancy BMI > 30 kg/m2 (obese) had a greater incidence of Bacteroidetes (incidence rate ratio [IRR]: 3.70 [95% CI: 1.61–8.48]) and a reduced incidence of Proteobacteria (0.62 [0.43–0.90]) in their milk, compared to women with an overweight BMI (25.0–29.9 kg/m2) as assessed by multivariable Poisson regression. An increased incidence of Gemella was observed among mothers with gestational diabetes who had an overweight BMI versus healthy range BMI (5.96 [1.85–19.21]). An increased incidence of Gemella was also observed among mothers with impaired glucose tolerance with an obese BMI versus mothers with a healthy range BMI (4.04 [1.63–10.01]). An increased incidence of Brevundimonas (16.70 [5.99–46.57]) was found in the milk of women who underwent an unscheduled C-section versus vaginal delivery. Lastly, functional gene inference demonstrated that pre-pregnancy obesity was associated with an increased abundance of genes encoding for the biosynthesis of secondary metabolites pathway in milk (coefficient = 0.0024, P FDR