Instrument and system for rapid microorganism identification and antimicrobial agent susceptibility testing
Inventors
Richards, William L. • Ashby, Austin • Ketterer, Matthew • Marshall, Kevin • Harrison, Josh • Mette, Matthew • Richards, Paul • Showalter, Wayne • Cote, Jasmin • Metzger, Steven W. • Hance, Ken • Mensack, Meghan • Michel, Carlos • Allers, Elke • Gamage, Dulini • Prisbrey, Landon • Gusyatin, Oleg • Shamsheyeva, Alena • Turng, Ben • Ghusson, Andrew • Reinhardt, Kurt • Halbert, Phillip C. • Bourgeois, Solene
Assignees
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Publication Number
US-10669566-B2
Publication Date
2020-06-02
Expiration Date
Abstract
A system for automated microorganism identification and antibiotic susceptibility testing comprising a reagent cartridge, a reagent stage, a cassette, a cassette, stage, a pipettor assembly, an optical detection system, and a controller is disclosed. The system is designed to dynamically adjust motor idle torque to control heat load and employs a fast focus process for determining the true focus position of an individual microorganism. The system also may quantify the relative abundance of viable microorganisms in a sample using dynamic dilution, and facilitate growth of microorganisms in customized media for rapid, accurate antimicrobial susceptibility testing.
Core Innovation
The invention relates to a method of identifying microorganisms in a patient sample using an automated microorganism identification and antibiotic susceptibility testing system with a cassette having a plurality of microfluidic channels. The method introduces the patient sample into the plurality of microfluidic channels and introduces, into each microfluidic sample channel, one or more labeled universal control nucleic acid probes and one or more labeled target nucleic acid probes that recognize and hybridize microorganism nucleic acid molecules.
After hybridization, the system captures images of multiple fields of view of one or more microorganisms hybridized to the labeled universal control nucleic acid probes and the labeled target nucleic acid probes using an optical detection system. Morphokinetic analysis is performed to identify characteristics of the one or more imaged microorganisms, and data from the morphokinetic analysis are inputted to a probability expectation model of distribution to identify one or more microorganisms in the patient sample.
The probability expectation model identifies microorganisms based on a combination of posterior probabilities from multiple of the microfluidic sample channels. Identification is additionally performed by matching a signal pattern of an unknown microorganism with a posterior probability density function of a labeled target nucleic acid probe using an empirical threshold value.
Claims Coverage
The document includes one independent claim covering a microfluidic probe hybridization workflow with morphokinetic analysis and posterior-probability-based identification across multiple microfluidic channels.
Microfluidic multiplexed probe hybridization in universal control and target channels
Introducing a patient sample into a plurality of microfluidic channels of a cassette; introducing into each microfluidic sample channel one or more labeled universal control nucleic acid probes and one or more labeled target nucleic acid probes that recognize and hybridize microorganism nucleic acid molecules; and incubating for a time sufficient to enable hybridization.
Imaging multiple fields of view with optical detection and morphokinetic analysis
Capturing images of multiple fields of view of one or more microorganisms hybridized to the labeled universal control nucleic acid probes and the labeled target nucleic acid probes with an optical detection system; and performing morphokinetic analysis to identify characteristics of the one or more imaged microorganisms.
Posterior-probability-based probability expectation model using combined channel posteriors
Inputting data from the morphokinetic analysis to a probability expectation model of distribution to identify one or more microorganisms in the patient sample, where identification is based on a combination of posterior probabilities from multiple of the microfluidic sample channels.
Empirical-threshold matching to posterior probability density function of a target probe
Matching a signal pattern of an unknown microorganism with a posterior probability density function of a labeled target nucleic acid probe using an empirical threshold value.
Across the independent claim, identification is grounded on multiplexed universal control and target nucleic acid probe hybridization in multiple microfluidic channels, optical imaging with morphokinetic analysis, and identification via a probability expectation model that combines posterior probabilities across channels, with an empirical threshold matching against a target probe posterior probability density function.
Stated Advantages
Documented Applications
Automated microorganism identification and antibiotic susceptibility testing using a system with microfluidic channels, labeled universal control and target nucleic acid probes, optical detection, morphokinetic analysis, and posterior-probability-based identification.
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