Antimicrobial Susceptibility Testing via Single Cell Trajectory Tracking
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Solution Overview
Problem
Current antimicrobial susceptibility testing methods are slow and unreliable, often requiring cell culture and enrichment, which can lead to false results due to the presence of impurities and the inability to detect new resistant strains, especially in samples with low bacterial counts.
Innovation Solution
The implementation of large volume scattering imaging (LVSi) for real-time tracking of single bacterial cell divisions in clinical samples, allowing for rapid identification of viable cells without the need for cell culturing or immobilization, and enabling precise antibiotic susceptibility testing by comparing cell division rates with and without antibiotics.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional AST methods use overnight cell culture and enrichment, then sensitivity is improved for detecting low bacterial counts, but time consumption increases and reliability decreases due to impurities and false positives
Solution Approach 1:
The patent extracts and isolates single bacterial cell division events from the complex clinical sample matrix by tracking individual cell trajectories. This extraction approach allows direct measurement of bacterial growth without requiring overnight culture or enrichment steps, achieving both rapid results (1-2 hours) and high reliability (97% accuracy) by focusing only on viable dividing cells while excluding impurities and dead cells
Solution Approach 2:
The patent replaces the traditional mechanical/cultural enrichment process with optical imaging and computational trajectory analysis. Instead of relying on bacterial culture growth over nights, the system uses scattering imaging to capture cell positions over time and algorithms to identify division events, substituting a physical culture-based system with an optical-detection-based system that delivers results in hours
2Measurement precision
If DNA/RNA copy changes or cell number changes are used to quantify cell growth, then measurement capability is improved, but reliability worsens due to interference from particulate contaminants and crystals
Solution Approach 1:
The patent segments the measurement approach by tracking individual bacterial cell trajectories separately rather than measuring bulk DNA/RNA or total cell counts. By dividing the sample into discrete trackable entities and monitoring each cell's position over time, the system can identify division events through trajectory analysis, achieving precise measurement of viable cell growth while ignoring non-biological particulates that cannot exhibit division patterns
Solution Approach 2:
The patent introduces trajectory analysis as an intermediary between raw imaging data and cell growth measurement. Instead of directly counting cells or measuring DNA, the system uses trajectory patterns as a mediator to infer division events, where only objects exhibiting characteristic division trajectories are counted, effectively filtering out contaminants and crystals that lack such patterns
3Reliability
If genotypic approaches detect antibiotic resistance genes, then sensitivity is improved for known pathogens, but adaptability decreases when new resistant strains emerge and false positives increase
Solution Approach 1:
The patent changes the measurement parameter from genetic presence (genotypic) to functional phenotypic expression (cell division inhibition). Instead of detecting resistance genes that may not be expressed, the system directly measures whether bacteria divide in the presence of antibiotics, a parameter that reflects actual functional resistance regardless of genetic background, enabling detection of both known and novel resistance mechanisms
Solution Approach 2:
The patent creates a universal testing approach that works for any bacterial pathogen without requiring pathogen-specific knowledge. The trajectory-based division measurement is a universal phenotypic readout applicable to all bacteria, making the system adaptable to emerging strains and novel resistance mechanisms while maintaining high sensitivity, unlike genotypic methods that require prior knowledge of specific resistance genes
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach provides rapid, accurate, and culture-free antimicrobial susceptibility testing, achieving 97% accuracy within one hour, effectively distinguishing between infection-positive and -negative samples and determining antibiotic susceptibility, even in low-concentration samples with high impurity levels.
Implementation Method 1
large volume scattering imaging (LVSi) for real-time tracking of single bacterial cell divisions
Data Source
AI summary
Detecting single bacterial cells in a sample includes collecting, from a sample provided to an imaging apparatus, a multiplicity of images of the sample over a length of time; assessing a trajectory of each bacterial cell in the sample; and assessing, based on the trajectory of each bacterial cell in the sample, a number of bacterial cell divisions that occur in the sample during the length of time.