Microfluidic Droplet Microorganism Quantification via AI Imaging
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Solution Overview
Problem
Current methods for quantifying microorganisms, such as plate counts and optical density measurements, are time-consuming, labor-intensive, and prone to errors, and do not accurately differentiate between live and dead microorganisms, leading to an unmet need for a faster and more accurate method.
Innovation Solution
A method involving encapsulating microorganisms in droplets using microfluidics, allowing growth, capturing images, and performing image analysis with artificial intelligence trained on machine learning algorithms to quantify microorganisms accurately.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If plate count method is used to quantify microorganisms, then accuracy of viable microorganism quantification is improved, but time consumption and labor intensity increase significantly
Solution Approach 1:
The invention divides the sample into multiple discrete droplets, each containing a small volume (e.g., 1 nL to 100 nL). This segmentation allows parallel processing of many samples simultaneously, increasing throughput while maintaining the accuracy of viable microorganism quantification through automated imaging and analysis of individual droplet colonies.
Solution Approach 2:
The invention replaces the manual mechanical processes of plate counting (spreading, incubation, manual colony counting) with an automated system using digital imaging and machine learning algorithms. The system captures images of droplet colonies and uses trained neural networks to automatically identify and count viable microorganisms, eliminating labor-intensive steps while maintaining accuracy.
2Speed
If optical density measurement is used to quantify microorganisms, then measurement speed is improved, but accuracy and ability to differentiate live vs dead microorganisms deteriorates
Solution Approach 1:
The invention utilizes visual characteristics (color, opacity, morphology) of microorganism colonies in droplets as they grow. By capturing images at specific time points and analyzing colony appearance characteristics, the system can differentiate between viable and non-viable microorganisms based on their growth patterns and visual properties, providing accurate quantification while maintaining rapid measurement capability.
3Measurement precision
If counting chamber method is used to quantify microorganisms, then direct counting capability is improved, but ability to distinguish live vs dead microorganisms and handle dilute cultures deteriorates
Solution Approach 1:
The invention performs preliminary enrichment by allowing microorganisms to grow into visible colonies within the droplets before counting. This preliminary growth action enables the detection of very low concentrations of microorganisms that would be difficult to detect directly, while the automated imaging system subsequently counts only the grown colonies, ensuring accurate quantification of viable organisms even in dilute samples.
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 high-precision, high-throughput quantification of viable microorganisms, reducing turnaround time and eliminating errors associated with conventional methods, enabling accurate determination of microorganism concentrations within samples.
Implementation Method 1
allowing microorganism growth within the one or more first droplets of the plurality of droplets
Data Source
AI summary
In aspects, the present disclosure provides methods for quantifying microorganisms. In aspects, the present disclosure provides methods for identifying microorganisms. In aspects, the present disclosure provides methods of analyzing food. In aspects, the present disclosure provides methods of treating a human subject having an infection. In aspects, the present disclosure provides methods of analyzing environmental samples.