Single-Cell Protein Quantification via Oligonucleotide Labeling and Pooling
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Solution Overview
Problem
Current methods for analyzing molecular targets from single cells face challenges due to minute quantities of molecular targets and biases introduced by conventional separation and analysis techniques, which limit the ability to accurately identify and quantify proteins and their post-translational modifications at the single-cell level.
Innovation Solution
The method involves labeling macromolecules within cells, pooling them to increase detectable amounts, separating and analyzing the labeled molecules using techniques like electrophoresis and mass spectrometry, and decoding oligonucleotide labels through sequencing to identify and quantify molecular targets at the single-cell level, thereby overcoming the limitations of conventional approaches.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional protein detection methods (Western blot, ELISA, mass spectrometry) are used, then detection sensitivity can be improved, but downscaling to single-cell level becomes difficult
Solution Approach 1:
The method segments the analysis into distinct identification and quantification steps. Cells are first labeled with unique oligonucleotide identifiers, then pooled for bulk protein extraction and separation. This segmentation allows conventional sensitive detection methods to be applied to pooled samples while maintaining single-cell resolution through the oligonucleotide labels.
Solution Approach 2:
Oligonucleotide labels serve as intermediaries between single cells and detection methods. These labels are attached to proteins from individual cells, allowing the proteins to be pooled and detected using conventional methods while the oligonucleotide identifiers preserve single-cell information throughout the process.
2Measurement precision
If separation methods enrich for certain molecular species, then detection of those species is improved, but relative abundances of components are distorted
Solution Approach 1:
The method uses oligonucleotide sequence counting as feedback to correct for separation biases. By counting the number of reads for each oligonucleotide identifier after separation and detection, the original relative abundances of proteins from different cells can be reconstructed even if the separation process enriched or depleted certain species.
Solution Approach 2:
The oligonucleotide labels act as information copies that are preserved through the separation process. Each protein molecule carries a copy of its cell's identifier, allowing the information about original abundances to be retained and read out after separation, independent of the separation biases affecting the proteins themselves.
3Adaptability or versatility
If antibody-based methods are used, then protein detection is enabled, but availability of good affinity reagents becomes the limiting factor
Solution Approach 1:
The oligonucleotide labels provide a universal tagging system that can be applied to any protein of interest through genetic fusion or biochemical labeling, eliminating the need for protein-specific antibodies. This universal approach enables detection of any protein that can be tagged with the oligonucleotide-containing construct.
Solution Approach 2:
The method replaces antibody-based recognition with oligonucleotide-based identification. Instead of relying on antibody-protein binding, the system uses sequence-specific oligonucleotide hybridization and sequencing to identify and quantify proteins, substituting a more versatile and manufacturable reagent system.
4Measurement precision
If material from single cells is used, then single-cell resolution is achieved, but enough material for analysis is not provided
Solution Approach 1:
The method merges proteins from multiple labeled cells into a single pooled sample for bulk extraction and separation. By combining material from many cells that carry unique oligonucleotide labels, sufficient total material is obtained for sensitive detection while the individual cell identities are preserved in the oligonucleotide sequences for subsequent deconvolution.
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 highly multiplexed and quantitative analysis of molecular species in single cells with high detection efficiency, preserving cellular origins and avoiding biases, allowing for the accurate quantification of post-translational modification isoforms with up to 40% detection efficiency.
Implementation Method 1
separating and analyzing the labeled molecules using techniques like electrophoresis and mass spectrometry
Implementation Method 2
separating and analyzing the labeled molecules using techniques like electrophoresis and mass spectrometry
Implementation Method 3
decoding oligonucleotide labels through sequencing to identify and quantify molecular targets at the single-cell level
Data Source
AI summary
The present application describes compositions and methods for identifying and quantitating molecular targets within a cellular environment. Specifically, provided herein are compositions and methods for separately identifying and quantifying each of one or more molecular targets from a single cell. More specifically, provided herein are compositions and methods for separately identifying and quantifying the same molecular target from a single cell.