## 1 Introduction
In the food production scenario, there is concern about these resistant microorganisms in foods originating from environmental contamination [29]. The contamination of microorganisms in cheese must also be seen from another perspective, based on the presence of BHMT. This group of bacteria produces metabolites that are not initially harmful to the health of the consumer but harm and alter the sensorial quality of the cheese, making it less appealing to consumers [30; 31]. However, [PERSON] et al. [32] correlated the presence of bacterial metabolites, such as pigments, with human illnesses in their study. The genus _Pseudomonas_ can produce proteases and lipases that interfere with the ripening process and cause sensory changes in cheese [30; 31]. Another important genus in this context is _Acinetobacter_, which can influence the color of the cheese by producing a brown pigment [33]. The application of bioinformatics, in addition to sequencing, accelerates and facilitates microbial identification compared to current methods [34] and enhances taxonomic classification through the use of specific genetic biomarkers [35]. This approach to analyzing bacterial community composition has already been applied in several studies with different types of foods [36; 37; 38; 39; 40; 41; 42; 43]. The identification of the microbial profile of the food matrix allows us to understand the \"history\" of the product [44], and omics and biomolecular techniques have gained prominence in this characterization. Metagenomics emerges as one of these techniques, focusing on the direct analysis of genetic material present in a given habitat without the need to isolate and culture each microorganism, providing a more comprehensive view of the genetic diversity and microbial potential present [45; 46; 47]. From the identification of the microbiota, several approaches seek to better understand the cheese ecosystem and clarify population and metabolic interactions to assist in cheese manufacturing [48]. In this same context, bioinformatics tools emerged, such as the pangenome, aimed at identifying and characterizing genes and proteins with potential application in the diagnosis, prevention, and therapy of infectious diseases [49]. The pangenome approach focuses on analyzing all the genes found in the metagenome sequencing, characterizing those present in all microorganisms (core genome), those that appear in some but not in all microorganisms (accessory genome), and species-specific ones (singletons or unique genomes) [50]. This approach allows for the selection of proteins with specific subcellular localization essential for the survival of microorganisms [51], thus enabling the development of techniques for rapid detection and creating mechanisms and technologies for inhibiting pathogens by improving quality control [49; 52]. This study aimed to characterize the diversity of bacterial groups present in sheep cheese, including bacteria with potential pathogenic and/or harmful effects on dairy technology, as well as to correlate the presence of these bacteria with the PC characteristics, the production of VOCs, and the FA profile of the cheese. Additionally, we sought to investigate and prospect, through genomic techniques, the presence of virulence, resistance, and toxin genes in reference genomes available in databases. The importance of this study for the dairy production chain and for consumer health is notable, revealing innovative information regarding the presence, in sheep's cheese, of potential pathogens and bacteria that can harm milk technology, through modern molecular biology techniques.