Opportunity
Current spatial transcriptomics and post-transcriptional profiling techniques face significant limitations in analyzing tissue-wide molecular heterogeneity at single-cell resolution. Conventional methods, such as fluorescence in-situ hybridization (FISH) and spatial transcriptomics, are either limited to small-scale cellular analysis or require complex tissue pre-treatment (e.g., frozen sectioning, fixation, membrane permeabilization), which can lead to RNA degradation and loss of spatial accuracy. Additionally, existing technologies struggle to simultaneously profile multiple post-transcriptional targets (e.g., microRNAs (miRNAs) and methylated mRNAs (mA mRNAs)) with subcellular resolution across large tissue samples. There is a critical need for a high-throughput, sequencing-free platform capable of capturing spatial and molecular heterogeneity in intact tissues without compromising resolution or introducing artifacts.
Technology
This patent introduces an innovative platform combining functionalized nanoprobe arrays and a digital spectrum barcoding system to achieve large-scale, single-cell post-transcriptional profiling. The nanoprobes, functionalized with target-specific "bait" molecules (e.g., p19 proteins for miRNAs, anti-mA antibodies for methylated mRNAs), penetrate fresh tissue samples to extract intracellular molecules while preserving spatial context. A UV imprinting step records tissue morphology on the nanoprobe array, enabling precise registration of molecular data to cellular locations.
The extracted targets are quantified using spectrum barcoding, where nanobeads conjugated with fluorophores at predefined ratios hybridize to targets. Machine learning decodes the spectral signatures, allowing multiplexed detection of multiple targets (e.g., 24 miRNAs and 9 mA mRNAs) in a single run. The system’s binary or trinary encoding strategy (using 4–7 fluorophores) enables high throughput (e.g., 15–10,000 codes) without super-resolution microscopy.
Advantages
- High-throughput multiplexing: Detects multiple molecular targets (miRNAs, mA mRNAs, proteins) simultaneously.
- Single-cell resolution: Maps expression patterns across entire tissue sections with subcellular precision.
- Minimal sample preparation: Works with fresh tissues, avoiding artifacts from fixation or sectioning.
- Sequencing-free: Uses fluorescence-based barcoding instead of sequencing, reducing cost and complexity.
- Scalable: Modular design accommodates additional targets or fluorophores.
- Machine learning integration: Automated decoding improves accuracy and throughput.
Applications
- Neuroscience: Profiling spatial heterogeneity of miRNAs and RNA methylation in brain regions (e.g., olfactory bulb).
- Cancer research: Identifying tumor microenvironment signatures at single-cell resolution.
- Developmental biology: Tracking post-transcriptional regulation during tissue differentiation.
- Drug discovery: Validating target engagement and spatial distribution of therapeutics.
- Diagnostics: Detecting disease-specific molecular patterns in biopsies.
