Microfluidic SEC-RPLC Biomarker Capture

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Solution Overview

Problem

Current methods for mass spectrometry analysis are inadequate in capturing a wide spectrum of proteins and other biomolecules from biological samples, particularly in capturing low-abundance proteins and handling highly complex samples like human blood, which limits the discovery of biomarkers for diseases.

Innovation Solution

A method involving size-exclusion chromatography (SEC) and reversed-phase liquid chromatography (RPLC) using microfluidic devices, with the inclusion of a chaotropic agent and viscosity modifying agent, to process biological samples, allowing for the unbiased capture and analysis of a diverse range of biomolecules, including proteins and metabolites, and enabling the identification of disease-specific biomarkers.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Adaptability or versatility

If conventional mass spectrometry methods are used to analyze biological samples, then the analysis process is simple, but the ability to capture a wide spectrum of proteins and biomolecules is insufficient

Engineering Contradiction:
Improveability to capture wide spectrum of biomoleculesVSAvoidcomplexity of sample processing method
Core Design Contradiction:
Adaptability or versatilityVSDevice complexity

Solution Approach 1:

The sample analysis is divided into multiple sequential chromatography steps (SEC followed by RPLC), where each step separates different aspects of the complex biological sample. This segmentation allows comprehensive coverage of diverse biomolecules while managing complexity through systematic multi-stage processing

Inventive Principle:
Principle #1Segmentation

Solution Approach 2:

The patent implements nested chromatography by placing RPLC within the SEC workflow, where RPLC analyzes fractions already separated by SEC. This nested approach enables multi-dimensional separation of biomolecules, capturing a wider spectrum of proteins and metabolites through hierarchical analysis

Inventive Principle:
Principle #7Nested doll (Nesting)

2Measurement precision

If conventional methods are used to analyze complex biological samples, then the method is easy to operate, but the detection precision for low-abundance proteins is insufficient

Engineering Contradiction:
Improvedetection precision of low-abundance proteinsVSAvoidease of sample processing
Core Design Contradiction:
Measurement precisionVSEase of operation

Solution Approach 1:

By segmenting the sample into size-based fractions through SEC before RPLC analysis, low-abundance proteins are separated from high-abundance interferents. This segmentation enhances detection precision by reducing background noise while maintaining operational simplicity through automated fraction collection

Inventive Principle:
Principle #1Segmentation

Solution Approach 2:

SEC acts as an intermediary step between sample introduction and RPLC-mass spectrometry analysis. This intermediate separation stage improves precision for low-abundance protein detection by pre-concentrating target analytes and removing masking substances, while the automated nature of SEC maintains ease of operation

Inventive Principle:
Principle #24Intermediary (Mediator)

3Quantity of substance

If comprehensive biomolecule capture is attempted, then the spectrum of detected biomolecules increases, but the complexity of data analysis increases

Engineering Contradiction:
Improvediversity of biomolecules detectedVSAvoidcomplexity of data analysis system
Core Design Contradiction:
Quantity of substanceVSDevice complexity

Solution Approach 1:

The multi-stage chromatography process segments the complex biological sample into manageable size-based fractions, reducing data complexity. Each fraction contains a subset of biomolecules that can be analyzed independently, making comprehensive data analysis more tractable while maintaining high diversity of detected substances

Inventive Principle:
Principle #1Segmentation

Solution Approach 2:

The patent adds a size-based separation dimension (SEC) to the traditional RPLC-mass spectrometry workflow. This additional dimensional separation organizes the complex data by molecular size, creating a structured data landscape that facilitates analysis of diverse biomolecules through multi-dimensional data organization

Inventive Principle:
Principle #17Another dimension (Dimensionality change)

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 enables comprehensive and reproducible analysis of biological samples, effectively capturing a wide spectrum of proteins and other biomolecules, even those at low abundance, facilitating the discovery of disease-specific biomarkers and improving the accuracy of mass spectrometry results.

Implementation Method 1

subjecting the test sample to a size-exclusion chromatography (SEC) technique using a SEC microfluidic device

Methodology Applied
Scientific EffectSize-exclusion chromatography: Chromatography

Implementation Method 2

subjecting one or more fractions from one or both of steps (b) and (c) to a reversed-phase liquid chromatography (RPLC) technique using a RPLC microfluidic device

Methodology Applied
Scientific EffectReversed-phase liquid chromatography: Chromatography

Implementation Method 3

the test sample comprises one or more biomolecules and a chaotropic agent

Methodology Applied
Scientific EffectChaotropic effect:

Data Source

PatentUS20240103007A1Mass spectrometry sample processing methods, chromatography devices, and data analysis techniques for biomarker analysis
Publication Date: 2024.03.28 PROTEAS BIOANALYTICS INC
  • US20240103007A1 patent drawing
  • US20240103007A1 patent drawing
  • US20240103007A1 patent drawing

AI summary

In certain aspects, the present disclosure is directed to platforms, including methods, devices, and components thereof, for processing samples for mass spectrometry. In other aspects, provided herein are analysis platforms for analyzing mass spectrometry data, including that obtained from mass spectrometry analysis of the samples obtained from the methods and devices described herein. In other aspects, provided are identified proteomic signatures of a condition in an individual, such as a coronary artery disease (CAD) proteomic signature.