RNA-Targeted Proximity Mapping (lncRNA/circRNA/miRNA/tRF-tiRNA/mRNA)
Define protein and RNA neighborhoods around specified transcripts in live cells for RNA-centric spatial interactomics.
Hybridization-Proximity Labeling (HyPro-MS) Service
RNA-Targeted Proximity Mapping in Live Cells
Hybridization–Proximity Labeling Mass Spectrometry (HyPro-MS) is a next-generation RNA-targeted interactomics platform designed for spatial resolution of RNA–protein–RNA neighborhoods. Unlike traditional RIP/CLIP methods, HyPro-MS captures proximity in living cells—preserving weak or transient associations, and revealing molecular contexts within biomolecular condensates such as stress granules or P-bodies.
We help researchers and CRO project teams:
- Identify proteins and RNAs near a specific lncRNA, miRNA, circRNA, or mRNA
- Resolve spatial interactomes under conditions like stress, drug response, or gene perturbation
- Profile live-cell condensate dynamics with dual LC–MS/MS and RNA-seq data
- Overcome transfection barriers with enzyme-based probe delivery
With high specificity (~20 nm), dual-omics capability, and compatibility with primary cells and difficult samples, HyPro-MS enables functional proximity insights unattainable through direct binding assays alone.
What Is Hybridization-Proximity Labeling (HyPro)-MS?
HyPro-MS is an RNA-targeted proximity labeling approach for spatial interactomics. A DIG-tagged DNA probe hybridizes to a chosen RNA. A fusion enzyme (APEX2 linked to a DIG-binding protein) docks on the probe and catalyzes biotin formation around the RNA target. Nearby proteins, RNAs, and potentially DNA within a short radius are biotinylated in live cells. The biotinylated molecules are enriched with streptavidin beads and identified by RNA-seq and LC–MS/MS.
This live-cell workflow captures weak or transient interactions and resolves RNA-centered networks inside biomolecular condensates formed by liquid–liquid phase separation (e.g., stress granules, P-bodies). It complements traditional RIP/CLIP or co-IP by adding spatial context.
Typical Scientific Questions HyPro-MS Can Answer
- Which proteins, RNAs, or chromatin regions reside near a specific lncRNA, circRNA, miRNA, tRF/tiRNA, or mRNA in live cells?
- How do proximity partners of a target RNA change under stress, stimulation, or compound exposure?
- Which RNA–protein assemblies are enriched inside stress granules, P-bodies, or other condensates?
- Do enhancer RNAs or SE-lncRNAs colocalize with defined transcriptional regulators in proximity?
- How do m6A readers reshape RNA-proximal interactomes impacting transcription, splicing, stability, or translation?
Advantages of Our HyPro-MS Service
Nanometer-scale specificity (~20 nm radius)
Biotinylation is confined to a short diffusion distance around the hybridized probe, enriching true neighbors while limiting off-target carryover.
Live-cell, native-state labeling
Proximity partners are captured in situ without extraction-first disruption, preserving weak or transient associations typical of condensates.
Enzymatic signal amplification
APEX2 catalysis generates abundant biotin tags near the target, improving downstream recovery and detectability after streptavidin enrichment.
Dual-omics confirmation in one pull-down
Proteins (LC–MS/MS) and RNAs (sequencing) are identified from the same enriched material, enabling orthogonal cross-validation of candidates.
Lower background via tethered fusion design
Linking APEX2 to a DIG-binding module localizes activity to the probe–RNA complex, reducing mislocalization compared with untethered approaches.
Compatible with hard-to-transfect systems
Protein delivery of the HyPro enzyme supports primary cells, neurons, and complex tissues where genetic overexpression is impractical.
Condensate-aware interactomics
Captures proximity within stress granules, P-bodies, and other LLPS compartments, revealing mesoscale organization beyond direct binder lists.
Structured controls and statistics
Scrambled probes, enzyme-minus conditions, and replicate modeling differentiate specific proximity from matrix background for confident prioritization.
Technical Services
Service Scope
Workflow and Instrumentation
Input Requirements
Deliverables
How to Choose
FAQ
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HyPro-MS Services: What We Offer at Creative Proteomics
Condensate-Resolved Interactomics (LLPS: Stress Granules, P-Bodies)
Identify proximity partners within phase-separated compartments to reveal mesoscale organization and context-dependent assemblies.
Enhancer & SE-lncRNA / Chromatin Proximity
Profile co-regulators and chromatin-associated factors near eRNAs and SE-lncRNAs to clarify enhancer architecture and regulatory hubs.
Epitranscriptomic Reader–Centered Mapping (e.g., m6A Readers)
Assess how reader recruitment reshapes local RNA–protein communities influencing transcription, splicing, stability, and translation.
Small-RNA HyPro (miRNA/RISC; tRF/tiRNA)
Characterize AGO-centered microenvironments and small-RNA–linked pathways involved in stress responses and translational control.
Differential Proximity Profiling (State, Treatment, Timepoint)
Compare RNA-proximal interactomes across conditions to generate mechanism-of-action hypotheses and prioritize candidates.
Assay Design: Probe Strategy & Specificity Controls
Design DIG-labeled probe sets and implement scrambled/enzyme-minus/competition controls to maximize specificity and interpretability.
Dual-Omics Proximity Identification & Analysis
Integrate LC–MS/MS proteomics and RNA sequencing on enriched material to deliver ranked candidates, enrichment statistics, and pathway context.
Step-by-Step Workflow for HyPro-MS Proximity Labeling
1
Target definition & probe design
Select the RNA of interest; design DIG-tagged complementary DNA probe(s) for specific hybridization.
2
Live-cell labeling
Deliver the HyPro fusion enzyme; allow probe docking; initiate APEX2-mediated biotinylation around the RNA target.
3
Capture & fractionation
Enrich biotinylated molecules with streptavidin magnetic beads; separate protein and RNA fractions for downstream assays.
4
Multi-omics identification
- Proteins: LC–MS/MS with high-resolution/accurate-mass detection.
- RNAs: Library preparation and sequencing; count-based differential proximity analysis.
5
Bioinformatics & quality control
Background modeling, enrichment statistics, contaminant filtering, functional annotation, network construction, and condensate-focused pathway analysis.
6
Reporting & recommendations
Deliver curated candidates, QC summaries, figures, and next-step experimental suggestions.
Technical Specifications and Instrumentation for HyPro-MS
HyPro-MS proximity labeling is powered by high-resolution mass spectrometry and RNA sequencing systems optimized for spatial interactome profiling.
Proteomics Platform
- Instrument: Orbitrap Exploris 480 or Q Exactive HF-X
- Acquisition Mode: Data-Dependent Acquisition (DDA) and Data-Independent Acquisition (DIA)
- LC System: nanoLC with C18 columns, optimized for 2–120 kDa proteins
- Quantification: Label-free or PRM-based targeted validation
RNA Sequencing Platform
- Instrument: Illumina NovaSeq 6000
- Library Type: Strand-specific, rRNA-depleted or poly(A)-enriched
- Read Depth: ≥30 million paired-end reads per sample
- Read Length: 2×150 bp for isoform-resolved mapping
Enrichment System
- Capture: Streptavidin magnetic beads
- Biotin Labeling Radius: ~20 nm proximity around the target RNA
- Buffer Conditions: Peroxidase-compatible, low-background protocols
Orbitrap Exploris 480
Q Exactive HF-X
Illumina NovaSeq 6000
Accepted Samples and Minimum Input for HyPro-MS Assays
| Item | Accepted Types | Minimum Amount | Pre-Labeling / State | Preservation & Shipping | Provide / Notes |
| Mammalian cells | Cell lines, primary cells, stem cells, neurons (adherent or suspension) | ≥ 4 × 107 cells | Live cells for on-site HyPro labeling; gently dissociated if adherent | Ice-cold buffers; ship on dry ice after lysis | Record media, supplements, treatments; avoid free biotin before labeling. |
| Fresh tissues | Human/animal research tissues | ≥ 300 mg | Thin slices for labeling or dissociated single cells | Fresh-frozen; RNase/DNase-free; dry ice shipping | Include species, anatomical site, collection method, storage history. |
| Post-labeling lysates (client-run) | Protein lysates after HyPro reaction | ≥ 1 mg total protein | Labeled; not boiled | Add protease/RNase inhibitors; snap-freeze; dry ice | Supply exact labeling protocol (reagents, timing, concentrations). |
| Bead-bound enrichments (optional) | Streptavidin pull-downs (client-run) | Beads from ≥ 1 mg input | Labeled; washed | Ship on cold packs or dry ice in low-biotin buffers | We can proceed to LC–MS/MS and/or RNA extraction from beads. |
| Nuclei preps (optional) | Isolated nuclei | From ≥ 4 × 107 cells | Intact nuclei | Ice-cold nuclei buffers; dry ice | For RNA–chromatin proximity or hard-to-lyse tissues. |
| RNA target info | Gene/transcript ID, target region, isoforms | — | Sequence metadata | Upload FASTA/CSV/DOC | Accessible 100–200 nt windows preferred; share known structure domains. |
| Controls | Scrambled probe, enzyme-minus, competition probe | — | Same matrix & handling as test | Ship with samples | Required for specificity benchmarking. |
Deliverables: What You Get from Our HyPro-MS Service
- Quantified Protein List: Proximity-enriched proteins with fold change, p-values, and annotations.
- Proximal RNA List: Differentially enriched RNAs near the target, with isoform-level resolution.
- Raw Data Files: LC–MS/MS (.raw), RNA-seq (.fastq), and processed result tables (.xlsx/.csv).
- QC Summary: Probe efficiency, enrichment success, replicate correlation, and background metrics.
- Visual Reports: Volcano plots, heatmaps, network graphs, and proximity pathway diagrams.
- Method Notes: Detailed experimental conditions, probe sequences, and labeling parameters.
Volcano Plot — Proximity-Enriched Proteins
Condition Matrix Heatmap — Differential Proximity
Integrated Network Map — RNA-Centered Interactome
Targeted Validation Panel — XIC + MS/MS (and RNA Track)
How to Choose: HyPro-MS vs. Alternative Interaction Technologies
| Research goal | Anchor (what's targeted) | Spatial context | Resolution | Primary outputs | Best first choice | Good complements | Watch-outs |
| RNA-centered live-cell proximity (incl. LLPS) | RNA (hybridized probe) | Yes (in situ) | Neighborhood (~tens of nm) | Proximal proteins + RNAs; condition deltas | HyPro-MS | APEX-seq (localization), ChIRP-MS (ex vivo capture), eCLIP (binding sites) | Not nucleotide-level binding sites |
| Direct protein→RNA binding sites | Protein (RBP) | Limited | Nucleotide (crosslinked sites) | Peak lists, motifs, target maps | eCLIP / PAR-CLIP | HyPro-MS for neighborhood context | Crosslink bias; misses transient neighbors |
| Protein complex composition (no RNA target) | Protein | No (ex vivo) | Complex/member level | Interactors, complex members | AP-MS / Co-IP | BioID/TurboID | May lose weak/transient partners |
| Protein-anchored proximity in cells | Protein | Yes (in situ) | Neighborhood (enzyme-dependent) | Proximal proteins | BioID / TurboID | AP-MS | Protein, not RNA, is the anchor |
| RNA–chromatin association / loci | RNA (sequence capture) | Genomic | Locus-resolved | DNA loci, chromatin partners | ChIRP / CHART / RAP | HyPro-MS | Harsher washes; less native dynamics |
| Global RNA localization maps | Compartment (enzyme tagging) | Yes (in situ) | Subcellular transcriptome | Compartment-level RNA profiles | APEX-seq | HyPro-MS for a single RNA's microenvironment | Not RNA-specific neighborhood mapping |
Practical tip: For mechanistic context around one RNA (stress, LLPS), start with HyPro-MS and validate top hits by eCLIP/RIP and targeted PRM. If exact binding sites are the KPI, begin with eCLIP/PAR-CLIP and add HyPro-MS for live-cell neighborhood context.
You May Want to Know
Does proximity labeling have known best practices or limitations I should consider?
APEX-family labeling and biotin-ligase methods are powerful for in-cell spatial mapping but require attention to background biotin, enzyme activity, and controls to avoid nonspecific carryover; matched negative controls and stringent washes are standard.
Can HyPro-MS work in hard-to-transfect cells or tissues?
Yes. Proximity labeling has been demonstrated in primary cells, neurons, and in vivo contexts using APEX2/TurboID variants, supporting applications where genetic overexpression is challenging when delivery is engineered appropriately.
How precise is the "neighborhood" captured by proximity labeling?
APEX2 and biotin-ligase–based methods are designed to tag molecules within a nanoscale radius around the bait; while the exact effective radius depends on enzyme/substrate kinetics and local environment, these tools have been validated for mapping subcellular microenvironments rather than whole-cell pools.
Can HyPro-MS reveal condensate (LLPS) biology like stress granules or P-bodies?
Yes. Proximity labeling is frequently used alongside LLPS research to profile components enriched within stress granules, P-bodies, and related RNP condensates, complementing imaging and biochemical fractionation.
When should I choose HyPro-MS over APEX-seq or Halo-seq?
Pick HyPro-MS when you need protein and RNA neighbors around one RNA in live cells; choose APEX-seq or Halo-seq when your priority is subcellular RNA localization at transcriptome scale rather than a single RNA’s microenvironment.
What controls are recommended for interpretation?
Use scrambled or non-target probes and enzyme-minus controls; for comparative studies, include matched conditions to support differential proximity analysis and mitigate matrix/background effects—an approach aligned with eCLIP/ENCODE control philosophy.
Will free biotin or certain reagents interfere with labeling?
Yes. Excess free biotin and some peroxidase inhibitors can reduce labeling efficiency or elevate background; low-biotin, enzyme-compatible buffers and clean media conditions are recommended before labeling.
How does HyPro-MS compare with BioID/TurboID?
HyPro-MS anchors the reaction to an RNA via hybridization, whereas BioID/TurboID are protein-anchored. TurboID offers fast ligase activity and broad applicability; projects sometimes combine RNA-anchored and protein-anchored maps to triangulate local neighborhoods.
What downstream readouts are typical for proximity-labeled material?
Proteins are identified by high-resolution LC–MS/MS and RNAs by sequencing; proximity labeling has been used to build subcellular proteome/transcriptome atlases and condition-specific neighborhood maps.
Can I study RNA–chromatin relationships with HyPro-MS?
HyPro-MS can suggest RNA–chromatin proximity via associated partners, but locus-resolved questions are best addressed with RNA hybrid-capture approaches (ChIRP/CHART/RAP) and then integrated with proximity datasets.