[en] Highlights: • Conventional pesticides as well as biological treatments shape the leaf microbiome of C. sinensis plants. • All investigated plants shared a large proportion of their microbiome (core microbiome). • The diversity within the bacterial communities was increased when the plants were subjected to disease control treatments. • Both treatments were distinguishable by specific microbial community fingerprints. -- Abstract: The plant microbiome is known to be influenced by certain biotic as well as abiotic factors. Nevertheless, the drivers for specific changes in microbial community composition and structure are largely unknown. In the present study, the effects of chemical and biological treatments for plant protection on the indigenous microbiome of Camellia sinensis (L.) Kuntze were contrasted. Assessment of bacteria-specific ribosomal RNA gene fragment amplicons from a representative set of samples showed an increased microbial diversity in treated plants when compared to untreated samples. Moreover, distinct microbial fingerprints were found for plants subjected to a conventional pesticide treatment with lime sulfur as well as for plants that were biologically treated with a Piriformospora indica spore solution. The bacterial community of pesticide-treated plants was augmented by 11 taxa assigned to Proteobacteria and Actinobacteria. In contrast, plants from biological control treatments were augmented by 10 taxa representing a more diversified community enrichment and included members of Actionobacteria, Proteobacteria, Bacteroidetes, Planctomycetes, and Verrucomicrobia. Complementary, molecular quantification of fungi in the samples showed a significantly lower number of internal transcribed spacer copies in plants subjected to biological control treatments, indicating the highest efficiency against fungal pathogens. The overall results show that leaves that are used for tea production show distinct microbiome shifts that are elicited by common pest and pathogen management practices. These shifts in the microbial population indicate non-target effects of the applied treatments.