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. 2024 Apr 17;90(4):e0223423.
doi: 10.1128/aem.02234-23. Epub 2024 Mar 18.

Exploring associations between the teat apex metagenome and Staphylococcus aureus intramammary infections in primiparous cows under organic directives

C J Dean  1 , F Peña-Mosca  1 , T Ray  1 , T J Wehri  2 , K Sharpe  2 , A M Antunes Jr  1 , E Doster  1 , L Fernandes  3 , V F Calles  1 , C Bauman  1 , S Godden  1 , B Heins  2 , P Pinedo  4 , V S Machado  3 , L S Caixeta  1 , N R Noyes  1
Affiliations

Exploring associations between the teat apex metagenome and Staphylococcus aureus intramammary infections in primiparous cows under organic directives

C J Dean et al. Appl Environ Microbiol. .

Abstract

The primary objective of this study was to identify associations between the prepartum teat apex microbiome and the presence of Staphylococcus aureus intramammary infections (IMI) in primiparous cows during the first 5 weeks after calving. We performed a case-control study using shotgun metagenomics of the teat apex and culture-based milk data collected longitudinally from 710 primiparous cows on five organic dairy farms. Cases had higher odds of having S. aureus metagenomic DNA on the teat apex prior to parturition compared to controls (OR = 38.9, 95% CI: 14.84-102.21). Differential abundance analysis confirmed this association, with cases having a 23.8 higher log fold change (LFC) in the abundance of S. aureus in their samples compared to controls. Of the most prevalent microorganisms in controls, those associated with a lower risk of post-calving S. aureus IMI included Microbacterium phage Min 1 (OR = 0.37, 95% CI: 0.25-0.53), Corynebacterium efficiens (OR = 0.53, 95% CI: 0.30-0.94), Kocuria polaris (OR = 0.54, 95% CI: 0.35-0.82), Micrococcus terreus (OR = 0.64, 95% CI: 0.44-0.93), and Dietzia alimentaria (OR = 0.45, 95% CI: 0.26-0.75). Genes encoding for Microcin B17 AMPs were the most prevalent on the teat apex of cases and controls (99.7% in both groups). The predicted abundance of genes encoding for Microcin B17 was also higher in cases compared to controls (LFC 0.26).

Importance: Intramammary infections (IMI) caused by Staphylococcus aureus remain an important problem for the dairy industry. The microbiome on the external skin of the teat apex may play a role in mitigating S. aureus IMI risk, in particular the production of antimicrobial peptides (AMPs) by commensal microbes. However, current studies of the teat apex microbiome utilize a 16S approach, which precludes the detection of genomic features such as genes that encode for AMPs. Therefore, further research using a shotgun metagenomic approach is needed to understand what role prepartum teat apex microbiome dynamics play in IMI risk.

Keywords: metagenomics; microbial ecology; veterinary epidemiology.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Fig 1
Fig 1
Sequencing and quality control plots of teat apex samples. (A) Raw sequencing depth as a function of sequencing batch; (B) raw sequencing depth as a function of case or control group and sequencing batch; (C) raw sequencing depth as a function of case or control group; (D) raw sequencing depth as a function of case or control group and days to infection; (E) raw sequencing depth as a function of case or control group and weeks to infection; (F) host sequencing depth as a function of sequencing batch; (G) host sequencing depth as a function of case or control group and sequencing batch; (H) host sequencing depth as a function of case or control group; (I) host sequencing depth as a function of case or control group and days to infection; (J) host sequencing depth as a function of case or control group and weeks to infection; (K) count of the number of teat apex samples by case or control group and days in milk; (L) count of the number of teat apex samples by case or control group and days to infection; (M) count of the number of teat apex samples by case or control group and weeks to infection; and (N) PCA plot of teat apex microbiome colored by sequencing batch.
Fig 2
Fig 2
Taxonomic composition, prevalence, and abundance of the most frequently sequenced microorganisms from the teat apex microbiome. The signature heatmap displays the median normalized abundance (clr, center-log ratio) of each microorganism for each week relative to infection in cases. The bar graph shows the prevalence of microorganisms in teat apex samples (denominator 839 samples). The dot plot shows the relative abundance of each microorganism within each sample. The red triangles represent the mean relative abundance of each microorganism across all samples.
Fig 3
Fig 3
(A) Forest plot describing the relationship between having an S. aureus intramammary infection and the odds of each species being present on the teat apex. Adjusted risks (Adj. Risk) represent the probability of the species being present on the teat apex, stratified by cases and controls. Odds ratios (OR) represent the odds of the species being present in cases relative to controls. The dashed vertical line in the forest plot indicates the null association. Points represent ORs and horizontal bars represent 95% confidence intervals. The number of samples (“frequency”, y-axis) with S. aureus in the teat apex metagenomic data (No = orange, Yes = blue) as a function of weeks to infection (B), days to infection (C), and days relative to calving (D).
Fig 4
Fig 4
(A) Bar plot displaying log fold change in abundance (x-axis) of each microorganism (y-axis) between cases and controls. Bars colored red indicate microorganisms with a significantly higher abundance in samples from cases compared to controls (i.e., risk factor); bars colored green indicate microorganisms with a significantly higher abundance in samples from controls compared to cases (i.e., protective); bars colored gray indicate microorganisms without a significant effect size (i.e., not sig). (B) Heatmap displaying normalized microbial abundances between cases and controls, stratified by farm. Abundances represent centered log ratios (i.e., clr).
Fig 5
Fig 5
Antimicrobial peptides detected in the teat apex shotgun metagenomic data. Genes encoding for AMPs were inferred by aligning translated sequence reads to the DRAMP protein database using PALADIN (32). AMP-encoded genes present in three or more samples are shown.
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