Background Mucosal healing is the therapeutic target for ulcerative colitis (UC). While amino acids (AAs) and the gut microbiota are known to be involved in the pathogenesis of UC, their specific roles in mucosal healing have not been fully defined. Objectives To longitudinally assess the changes in AA concentrations and the gut microbiota composition in the context of mucosal healing in UC patients, with the aim of identifying new biomarkers with predictive value for mucosal healing in UC patients and providing a new theoretical basis for dietary therapy. Methods A total of 15 UC patients with infliximab-induced mucosal healing were enrolled. Serum and fecal AA concentrations before and after mucosal healing were determined via targeted metabolomics. A receiver operating characteristic (ROC) curve was plotted to evaluate the value of different AAs in predicting mucosal healing in UC patients. The changes in the composition of the fecal gut microbiota were analyzed via metagenomics, and bioinformatics was used to analyze the functional genes and metabolic pathways associated with different bacterial species. Spearman correlation analyses of fecal AAs with significantly different concentrations and the differentially abundant bacterial species before and after mucosal healing were performed. Results 1. The fecal concentrations of alanine, aspartic acid, glutamic acid, glutamine, glycine, isoleucine, leucine, lysine, methionine, phenylalanine, proline, serine, threonine, tryptophan, tyrosine and valine were significantly decreased after mucosal healing. The serum concentrations of alanine, cysteine and valine significantly increased, whereas that of aspartic acid significantly decreased. Glutamic acid, leucine, lysine, methionine and threonine could accurately predict mucosal healing in UC patients, and the area under the curve (AUC) was > 0.9. After combining the 5 amino acids, the AUC reached 0.96. 2. There were significant differences in the gut microbiota composition before and after mucosal healing in UC, characterized by an increase in the abundance of beneficial microbiota (Faecalibacterium prausnitzii and Bacteroides fragilis) and a decrease in the abundance of harmful microbiota (Enterococcus faecalis). LEfSe analysis identified 57 species that could predict mucosal healing, and the AUC was 0.7846. 3. Amino acid metabolic pathways were enriched in samples after mucosal healing, was associated with the abundance of multiple species, such as Faecalibacterium prausnitzi, Bacteroides fragilis, Bacteroides vulgatus and Alistipes putredinis. 4. The fecal concentrations of several AAs were negatively correlated with the abundance of a variety of beneficial strains, such as Bacteroides fragilis, uncultured Clostridium sp., Firmicutes bacterium CAG:103, Adlercreutzia equolifaciens, Coprococcus comes and positively correlated with the abundance of several harmful strains, such as Citrobacter freundii, Enterococcus faecalis, Klebsiella aerogenes, Salmonella enterica. Conclusion Altered concentrations of amino acids and their associations with the gut microbiota are implicated in the mucosal healing of UC patients and can serve as noninvasive diagnostic biomarkers.