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Record W3126796699 · doi:10.1186/s42523-021-00081-9

Ruminal resistome of dairy cattle is individualized and the resistotypes are associated with milking traits

2021· article· en· W3126796699 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAnimal Microbiome · 2021
Typearticle
Languageen
FieldEnvironmental Science
TopicPharmaceutical and Antibiotic Environmental Impacts
Canadian institutionsUniversity of Alberta
FundersAgriculture Research System of ChinaZhejiang UniversityNational Natural Science Foundation of China
KeywordsResistomeBiologyRumenMicrobiomeAntibiotic resistanceMetagenomicsAntimicrobialMilkingUniFracBiotechnologyMicrobiologyFood scienceBacteriaAntibioticsAnimal scienceIntegronGeneticsGene

Abstract

fetched live from OpenAlex

Abstract Background Antimicrobial resistance is one of the most urgent threat to global public health, as it can lead to high morbidity, mortality, and medical costs for humans and livestock animals. In ruminants, the rumen microbiome carries a large number of antimicrobial resistance genes (ARGs), which could disseminate to the environment through saliva, or through the flow of rumen microbial biomass to the hindgut and released through feces. The occurrence and distribution of ARGs in rumen microbes has been reported, revealing the effects of external stimuli (e.g., antimicrobial administrations and diet ingredients) on the antimicrobial resistance in the rumen. However, the host effect on the ruminal resistome and their interactions remain largely unknown. Here, we investigated the ruminal resistome and its relationship with host feed intake and milk protein yield using metagenomic sequencing. Results The ruminal resistome conferred resistance to 26 classes of antimicrobials, with genes encoding resistance to tetracycline being the most predominant. The ARG-containing contigs were assigned to bacterial taxonomy, and the majority of highly abundant bacterial genera were resistant to at least one antimicrobial, while the abundances of ARG-containing bacterial genera showed distinct variations. Although the ruminal resistome is not co-varied with host feed intake, it could be potentially linked to milk protein yield in dairy cows. Results showed that host feed intake did not affect the alpha or beta diversity of the ruminal resistome or the abundances of ARGs, while the Shannon index ( R 2 = 0.63, P < 0.01) and richness ( R 2 = 0.67, P < 0.01) of the ruminal resistome were highly correlated with milk protein yield. A total of 128 significantly different ARGs (FDR < 0.05) were identified in the high- and low-milk protein yield dairy cows. We found four ruminal resistotypes that are driven by specific ARGs and associated with milk protein yield. Particularly, cows with low milk protein yield are classified into the same ruminal resistotype and featured by high-abundance ARGs, including mfd and sav 1866. Conclusions The current study uncovered the prevalence of ARGs in the rumen of a cohort of lactating dairy cows. The ruminal resistome is not co-varied with host feed intake, while it could be potentially linked to milk protein yield in dairy cows. Our results provide fundamental knowledge on the prevalence, mechanisms and impact factors of antimicrobial resistance in dairy cattle and are important for both the dairy industry and other food animal antimicrobial resistance control strategies.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.762
Threshold uncertainty score0.760

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.017
GPT teacher head0.245
Teacher spread0.228 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it