MATQ-Drop Microvolume Sequencing for Synaptosome Transcriptome Profiling
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Solution Overview
Problem
Current methods for transcriptome profiling of individual synaptosomes are limited by low RNA quantities, RNA leakage, and the inability to detect nascent RNA, making it challenging to characterize synaptic heterogeneity and construct a comprehensive synapse transcriptome atlas.
Innovation Solution
The development of a microvolume-based total-RNA sequencing platform, MATQ-Drop, which enables in situ reverse transcription and amplification of RNA sequences from fixed subcellular structures, allowing for the simultaneous detection of mature and nascent RNA, and the use of barcoded primers for spatial resolution and high-throughput profiling of millions of single subcellular structures.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional scRNA-seq platforms are used for transcriptome profiling, then single cell RNA detection is achieved, but individual synaptosomes cannot be successfully profiled due to smaller RNA quantities
Solution Approach 1:
The method segments the transcriptome profiling process into in situ reverse transcription within fixed synaptosomes followed by controlled release and amplification. This segmentation allows the reaction to occur in the confined space of individual synaptosomes, capturing all RNA molecules including those in low abundance, thereby improving detection sensitivity for subcellular structures with limited RNA quantity
Solution Approach 2:
The protocol performs preliminary fixation of synaptosomes before RNA extraction to prevent RNA leakage during subsequent processing steps. This preliminary action stabilizes the RNA within the synaptosome membrane, ensuring that even low-quantity RNA molecules are preserved and can be detected with high sensitivity
2Productivity
If synaptosomes are prepared for profiling, then subcellular structures are isolated, but RNA molecules leak significantly in downstream steps requiring immediate fixation
Solution Approach 1:
The method performs preliminary fixation of synaptosomes with paraformaldehyde before any downstream processing to prevent RNA leakage. This fixation step creates crosslinks that stabilize RNA within the synaptosome, preventing loss during subsequent enzymatic reactions and manipulations, thereby maintaining high RNA retention while enabling productive profiling
Solution Approach 2:
The protocol introduces an intermediary fixation step that acts as a protective barrier between the synaptosome RNA and the potentially disruptive downstream enzymatic reactions. This intermediary action prevents direct interaction between RNA and enzymes that could cause leakage, allowing productive profiling to proceed
3Adaptability or versatility
If mature RNA-based assays are used, then standard transcriptome profiling is achieved, but nascent RNA and locally spliced genes cannot be characterized
Solution Approach 1:
The method employs universal reverse transcription primers that can bind to both mature and nascent RNA molecules, enabling the same assay to detect multiple RNA types simultaneously. This multi-functionality allows characterization of both mature transcripts and nascent transcripts including locally spliced genes without requiring separate assays
Solution Approach 2:
The protocol changes the detection parameter from mature RNA-specific to total RNA-inclusive by using random hexamer primers during reverse transcription that can anneal to any RNA sequence regardless of processing status. This parameter change enables accurate detection and characterization of nascent RNA molecules alongside mature transcripts
4Productivity
If high-throughput profiling of millions of synaptosomes is desired, then large-scale analysis is achieved, but spatial resolution and individual structure identification become challenging
Solution Approach 1:
The method extracts unique molecular identifiers (UMIs) and barcodes from individual synaptosomes during the in situ reverse transcription step. Each synaptosome receives a unique molecular signature that is extracted and recorded, enabling later identification and spatial mapping of millions of individual structures while maintaining high throughput profiling capability
Solution Approach 2:
The protocol creates molecular copies of each synaptosome's transcriptome with embedded unique barcodes and UMIs. These copied molecular signatures serve as identifiers that can be read out later to reconstruct the spatial distribution and individual identity of millions of synaptosomes, maintaining both high throughput and spatial resolution
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
MATQ-Drop facilitates high-sensitivity transcriptome profiling of individual synaptosomes, enabling the identification of different subtypes and their association with neuronal types, and reveals novel gene expression changes associated with Alzheimer's disease, providing a powerful tool for neuroscience research.
Implementation Method 1
fixing cellular material (fresh, frozen, or was previously frozen) that is or comprises one or more subcellular structures such that RNA associated with the structure is affixed to the structure
Implementation Method 2
subjecting the subcellular structures and the RNA to first primers to generate a collection of first complementary polynucleotides that are complementary to one or more different regions in the RNA
Implementation Method 3
producing hybrid molecules between the RNA and first complementary polynucleotides
Data Source
AI summary
Embodiments of the disclosure include high-throughput profiling of transcriptomes of subcellular compartments or structures, including a droplet-based single-cell total-RNA-seq method that enables profiling of transcripts localized in particular subcellular compartment or structures. In specific embodiments, the disclosure provides for transcriptome profiling of single nuclei that allows for construction of a cell atlas using only long non-coding RNA species that can be applied for tissue-wide identification of cell-type-specific lncRNA species.