Time-consuming, expensive and low sensitivity diagnostic methods used for monitoring bacterial infections lead to unnecessary or delays in prescription of the right antibiotic treatment.Determining an optimal clinical treatment requires rapid detection and identification of pathogenic bacteria and their sensitivity to specific antimicrobials. However, diagnostic devices that meet all of these criteria have proven elusive thus far. Graphene field effect transistors (G-FET) are a promising solution, since they are highly sensitive to chemical/biological modification, can have fast detection times and can be placed on different substrates. Here, by integrating specific peptide probes over G-FETs, we present a proof-of-concept study for species and strain specific label-free detection of clinical strains of pathogenic bacteria with high specificity and sensitivity. We found that pyrene-conjugated peptides immobilized on G-FETs were capable of detecting pathogenic Staphylococcus aureus at the single-cell level and discriminate against other gram-positive and gram-negative bacterial pathogens. A similar device was able to discriminate between antibiotic resistant and sensitive strains of Acinetobacter baumannii, suggesting that these devices can also be used for detecting antibiotic resistive pathogens. Furthermore, a new means of enhancing attachment, electric-field assisted binding, reduced the detection limit to 10 4 cells/ml and the detection time to below 5 minutes. The combination of single step attachment, inexpensive production, rapid, selective and sensitive detection suggest G-FETs plus pyrene-conjugated peptides are a new platform for solving major challenges faced in point of care diagnostics to fight infectious diseases and antimicrobial resistance.Bacterial infections cause a wide range of diseases and significant mortality 1 . While antibiotics are key in controlling disease severity and reducing mortality, their over prescription and misuse are some of the most important factors in the surge of antibiotic resistant cases around the world. [2][3][4] In order to solve this crisis, diagnostic methods are needed that can rapidly and accurately identify the bacterium causing the infection and determine its associated antibiotic resistance profile. Antibiotic susceptibility testing (AST) is mostly carried out by phenotypic methods that require prior identification of bacterial pathogens from patients (at the species and/or strain level) and incubation under antibiotic conditions, 5, 6 a lengthy process that can take up to 24 hours to a month depending on the species. 7 Moreover, both species/strain identification and AST require trained specialists, specific laboratory environments and often expensive instrumentation. 5, 6, 8 Since these conditions limit widespread application and implementation into actual treatment strategies at most points of care, there is much room for improvement to develop new diagnostic devices that have the potential for adoption across a large variety of use cases. Ideally these dev...