FAST: Rapid determinations of antibiotic susceptibility phenotypes using label‐free cytometry

Abstract

Sepsis, a life-threatening immune response to blood infections (bacteremia), has a ∼30% mortality rate and is the 10th leading cause of US hospital deaths. The typical bacterial loads in adult septic patients are ≤100 bacterial cells (colony forming units, CFU) per ml blood, while pediatric patients exhibit only ∼1000 CFU/ml. Due to the low numbers, bacteria must be propagated through ∼24-hours blood cultures to generate sufficient CFUs for diagnosis and further analyses. Herein, we demonstrate that, unlike other rapid post-blood culture antibiotic susceptibility tests (ASTs), our phenotypic approach can drastically accelerate ASTs for the most common sepsis-causing gram-negative pathogens by circumventing long blood culture-based amplification. For all blood isolates of multi-drug resistant pathogens investigated (Escherichia coli, Klebsiella pneumoniae, and Acinetobacter nosocomialis), effective antibiotic(s) were readily identified within the equivalent of 8 hours from initial blood draw using <0.5 mL of adult blood per antibiotic. These methods should drastically improve patient outcomes by significantly reducing time to actionable treatment information and reduce the incidence of antibiotic resistance. © 2018 International Society for Advancement of Cytometry.

A fast impedance-based antimicrobial susceptibility test

“…In comparison, impedance cytometry is a label-free method that directly measures both cell volume (size) and other phenotypic changes that are reflected in the electrical signature. In iFAST, we observed changes in the electrical properties of cells due to the action of antibiotics such as β-lactams, whereas only small changes in optical scatter signal are observed using flow cytometry 16 , 44 , 45 . Unlike electrical techniques, optical methods indirectly determine cell volume from light scattering and the signal can be influenced by cell refractive index, shape, and orientation 46 , and by debris in the suspension.…”

PhenoGMM: Gaussian mixture modelling of microbial cytometry data enables efficient predictions of biodiversity

“…Because it is in an adaptive strategy as well, by defining small clusters in regions of high density and vice versa, it reduces the number of sample-describing variables considerably compared to fixed binning approaches. Other adaptive binning strategies have been proposed for microbial FCM data as well, however these still only investigate bivariate interactions (Amalfitano et al, 2018;Huang et al, 2018).…”

Evaluation of Antibiotic Resistance Pattern of Meropenem and Piperacillin- Tazobactam in Multi Drug Resistant Acinetobacter baumannii Isolates by Flow Cytometry Method

“…Flow cytometry (FCM) , is a device that passes cells or micrometer particles through the point of contact where the laser beams affect them, and the light that they absorb which is based on the intrinsic or sub-physical properties of the particle itself, Scatter or diffuse, and this light can be measured (1,2). Today, flow cytometry is a tool for bacterial analysis, detection, enumeration, determining changes in cellular function, metabolic activity, cell viability and antibiotic susceptibility of bacteria (3,32). Over the past decade, the presence of Acinetobacter baumannii, especially multiple drug resistant A. baumannii (MDRAB), has been recognized as the most important pathogen and cause of hospital mortality worldwide.…”