The rumen microbiome allows ruminants to feed on forages not adapted for monogastrics’ consumption. Nevertheless, ruminant production contributes to the greenhouse effect through the production of enteric methane by rumen archaea. The aim of this work was to get insight into how rumen microbes adapt and function when an anti-methanogenic compound inhibits methane production in cows. The experimental setup consisted of 25 lactating Holstein cows fed a total mixed ration of corn silage, grass hay and concentrate with (n= 12) or without (n= 13) a specific methane inhibitor. In week 5, rumen fluid samples were collected before the morning feeding from each cow via stomach tubing and subjected to RNASeq (Illumina HiSeq) and metabolomics (RPLC-QToF/MS, HILIC-Orbitrap, LC-MS/MS and GC-FID) analysis. In week 6, cows were transferred into respiration chambers for measuring methane emissions for 4 days. The MetaTrans pipeline was used for metatranscriptomic analysis and metabolomic data were processed using the web-based Galaxy Workflow4Metabolomics. KEGGs (mapped mRNA), OTUs (based on rRNA), and metabolomic data were integrated via causality relationships using Bayesian Networks. In the treated group, enteric methane emissions were reduced by 23%. Our initial analysis uncovered novel relationships between OTUs, KEGGs, and metabolites. The treated group of cows had two OTUs and 57 KEGGs differentially expressed, together with 39 discriminant metabolites, in comparison with control. After integration, the anaerobic carbon-monoxide dehydrogenase catalytic subunit, upregulated in the treated group, was related with the genera Methanosphaera, Butyrivibrio, Ruminococcus, and Methanobrevibacter, whose abundance did not differ significantly between the groups. This enzyme is involved in the initial step of carbon fixation in methanogens and acetogens. Other associations will be performed using this multi-omic approach and microbes associated with the decrease in methane emissions may be identified.