Bacterial pathogens and their association with diseases have long been major public health concerns around the world. It is estimated that 10 million people died of infectious diseases in 2016 [1, 2]. Our ability to identify and track these pathogens in the environment is important to understand their risks in the environment and our lives [3, 4]. Several approaches have been used to detect and identify pathogens in the environment. The culturedependent method, which selectively grows and isolates cultivable pathogens, has been considered as a standard methodology. The culture-dependent method has the advantage of widely accessible and cost-effective [5]. The challenge of this approach is that many pathogens in the environment exist in a viable but non-culturable (VBNC) state, which leads to limited detection and underestimation of total pathogens in the environmental samples [6, 7]. To circumvent these drawbacks, molecular biological tools such as real-time quantitative PCR (qPCR) and sequencing-based approaches have been adopted to detect and identify the bacterial pathogens in the environment [8-12]. qPCR is a highly sensitive and specific method to reliably quantify the pathogenic genes in the environment using gene probes designed to target specific genes of interest. qPCR method relies on the specificity and sensitivity of primer sets to amplify the target genes. Consequently, when the number of target genes is large or unspecified, this approach is not always appropriate to identify genes associated with pathogens in the environment due to both practical and economic reasons [13, 14]. Recently, shotgun high-throughput sequencing of metagenomes from environmental microbial communities has been applied to identify bacterial pathogens in diverse environments [11, 12]. Several curated databases and tools, including the Meta-multilocus sequence typing (MLST), virulence factor database (VFDB), and pathosystems resource integration center (PATRIC), have been developed to annotate pathogens in metagenomes [15-17]. Each database is used to identify bacterial pathogens based on sequence homology to genes associated The identification of bacterial pathogens to humans is critical for environmental microbial risk assessment. However, current methods for identifying pathogens in environmental samples are limited in their ability to detect highly diverse bacterial communities and accurately differentiate pathogens from commensal bacteria. In the present study, we suggest an improved approach using a combination of identification results obtained from multiple databases, including the multilocus sequence typing (MLST) database, virulence factor database (VFDB), and pathosystems resource integration center (PATRIC) databases to resolve current challenges. By integrating the identification results from multiple databases, potential bacterial pathogens in metagenomes were identified and classified into eight different groups. Based on the distribution of genes in each group, we proposed an equation to calculate the metagenom...