Sepsis is a leading cause of death worldwide, resulting from bacterial, fungal, or viral infections that affect vital organs. The emergence of antimicrobial resistance, particularly among gram-negative bacteria, complicates sepsis treatment. Metagenomic Next-generation Sequencing (mNGS), specifically nanopore sequencing with the MinION device, from Oxford Nanopore Technologies, shows promise for an early pathogen identification. This study aimed to evaluate the efficacy of mNGS for early sepsis diagnosis, optimize microbial DNA extraction from blood, and conduct species identification and antimicrobial resistance profiling in gram-negative bacteria. Blood samples from healthy volunteers had been collected and spiked with known microbial DNA before being extracted with three different DNA extraction kits. Following extraction and quality control, the DNA samples underwent library preparation and sequencing on a MinION device, which used both Flongle and MinION flow cells. The obtained data was analyzed using MinKNOW, enabling species identification via EPI2ME Fastq What's-In-My-Pot (WIMP) and the BV-BRC Taxonomic Classification Service. Additionally, the BV-BRC's Metagenomic Read Mapping Service was utilized to identify genes encoding antibiotic resistance. The nanopore sequencing effectively identified the known microbial composition in the blood samples, including all gram-negative bacteria and their antibiotic resistance genes. Efficient DNA extraction, quality control, and advanced bioinformatics tools were critical to data integrity. The accuracy and specificity of the WIMP workflow on the EPI2ME website were found to be flawed due to inaccuracies in the RefSeq database. These findings highlight the value of nanopore sequencing in sepsis management, with implications for better clinical outcomes. Additional research is needed to address existing limitations and improve the analysis of clinical samples.