Challenge Context — Why Traditional Approaches Falter
Conventional shotgun metagenomics, whether based on short-read or long-read sequencing, has transformed our ability to profile microbial communities. Yet when it comes to answering one of the most critical questions in microbiome science—"Which mobile genetic elements belong to which host?"—these methods fall short.
The core limitation lies in the DNA extraction step. Once the DNA is removed from the cell, plasmids, bacteriophages, integrons, and other mobile genetic elements (MGEs) become physically separated from their native microbial hosts. This disconnect prevents accurate mapping of horizontal gene transfer events and obscures strain-level dynamics.
Even with advanced binning algorithms, standard metagenomics struggles with:
- Ambiguous Host–MGE Assignments — ARGs, plasmids, and viruses are often detected but remain "unlinked" to a specific genome.
- Low Strain Resolution — Closely related strains collapse into mixed bins, hiding functional diversity.
- Contamination in Genome Bins — Misassigned contigs lead to incomplete or impure metagenome-assembled genomes (MAGs).
- Missed Ecological Insights — Without precise host association, the ecological roles of MGEs remain speculative.
Meta-Hi-C and Meta-3C overcome these obstacles by capturing DNA–DNA proximity within intact cells, preserving the native spatial context of microbial chromosomes, plasmids, and phages. This enables researchers to reconstruct high-purity MAGs and build accurate host–MGE interaction networks, unlocking insights that remain inaccessible to conventional approaches.
Principles & Innovation of Meta-Hi-C / 3C
Chromatin conformation capture for metagenomics brings a spatial dimension to microbial genome analysis. Both Meta-Hi-C and Meta-3C are designed to preserve in-cell DNA proximity before sequencing, allowing contigs from the same organism to be clustered with exceptional accuracy.
How Meta-Hi-C Works
- In-Cell Crosslinking — Formaldehyde or similar agents fix DNA in its native three-dimensional structure inside the cell.
- Restriction Digestion & Ligation — Enzymes cut the DNA, and physically proximate ends are ligated, creating chimeric junctions that capture true biological proximity.
- Library Preparation & Sequencing — Ligation products are sequenced, typically alongside shotgun metagenomic reads.
- Proximity-Guided Binning — Hi-C contact frequencies guide the clustering of contigs into high-purity MAGs, resolving strains and linking MGEs to hosts.
Meta-Hi-C excels when high-quality metagenome assemblies are available, offering low contamination rates and precise MGE–host linkage.
How Meta-3C Differs
- Multiple Restriction Enzymes — Utilizes three enzymes with distinct recognition sites (e.g., AATT, GGCC, GATC) to achieve balanced GC coverage across diverse taxa.
- No Biotin Labelling Required — Simplifies experimental workflow and reduces sample handling steps.
- Standalone Analysis Capability — Can reconstruct and bin genomes using only Meta-3C data, even without prior shotgun sequencing.
This flexibility makes Meta-3C ideal for projects with limited sequencing budgets or for environments where diverse GC content would otherwise bias coverage.
Innovative Advantages Over Conventional Metagenomics
- Preserves Spatial Context — Maintains physical linkage between MGEs and their microbial hosts.
- Strain-Level Discrimination — Separates near-identical strains within complex communities.
- MGE Host Mapping — Links plasmids, bacteriophages, integrons, and ARGs directly to host genomes.
- Enhanced Assembly Confidence — Reduces chimeric bins and supports confident downstream functional annotation.
Service Format — Tailored Solutions for Researchers
Different research projects have different starting points. Whether you already have a high-quality metagenome assembly or you are working with raw environmental samples, our Meta-Hi-C and Meta-3C platforms can be adapted to your study design.
Option 1 —Hi-C Metagenomics Enhanced Metagenomics
Ideal for researchers with existing shotgun metagenomic data or plans to sequence it in parallel.
- Workflow: Hi-C chromatin interaction library prepared from your sample → Sequencing → Integration with metagenome assembly → Hi-C guided binning and host–MGE association.
- Strengths:
- Low contamination, high-purity MAG recovery.
- Superior strain resolution.
- Excellent for high-complexity samples requiring detailed MGE mapping.
Option 2 — Meta-3C (Chromosome Conformation Capture) Standalone Genome Reconstruction
For projects without prior metagenomic sequencing, or when a streamlined workflow is preferred.
- Workflow: Three independent 3C libraries prepared with complementary restriction enzymes → Sequencing → Genome reconstruction and binning directly from Meta-3C data.
- Strengths:
- Eliminates the need for separate shotgun data.
- Balanced GC coverage across diverse microbial taxa.
- Reduced handling steps for sensitive or difficult samples.
Why We Offer Both
Some studies benefit from Meta-Hi-C's integration with long- or short-read assemblies, especially when aiming for near-complete genomes. Others demand the self-sufficiency and flexibility of Metagenomic 3C (Chromosome Conformation Capture) in field studies or pilot surveys. By offering both, we enable you to choose a method that fits your sample type, research goals, and data requirements—without compromise.
Service Workflow — From Inquiry to Data Delivery
Bioinformatics Analysis — From Raw Reads to Research-Ready Insights
High-quality sequencing data is only the starting point. To extract meaningful biological insights, our bioinformatics pipeline transforms raw chromatin interaction reads into precisely reconstructed genomes and verified host–MGE associations.
1. Data Quality Control
- Removal of low-quality reads, adapters, and chimeric ligation artifacts.
- Validation of read-pair orientation and proximity signal strength.
2. Proximity-Guided Genome Binning
- Mapping Hi-C/3C reads to assembled contigs or de novo reconstructed scaffolds.
- Clustering based on normalized contact frequency matrices.
- Optimization to minimize contamination and maximize completeness.
3. MGE–Host Association Mapping
- Identification and annotation of plasmids, bacteriophages, and integrons.
- Linking of antimicrobial resistance genes (ARGs) to their verified host genomes.
- Construction of host–MGE interaction networks for visualization and comparative analysis.
4. Functional and Comparative Genomics
- Gene annotation and pathway mapping using curated reference databases.
- Comparative genomics to track strain-specific features or horizontal gene transfer events.
- Optional integration with metatranscriptomics for functional activity profiling.
5. Output-Ready Deliverables
- Interactive network maps of phage–host and plasmid–host relationships.
- High-purity MAG files, annotation tables, and detailed QC reports.
- Publication-ready figures for immediate inclusion in manuscripts or presentations.
Sample Requirements — Ensuring Data Integrity from the Start
| Sample Type |
Minimum Amount |
Handling & Storage |
Notes |
| Human feces |
~1 g per tube, 3–5 replicate tubes |
Collect fresh, store at –80°C, ship on dry ice |
Avoid preservatives unless pre-approved |
| Animal feces (e.g., mouse) |
5 pellets per tube, 3–5 replicate tubes |
Same as above |
Use sterile collection tools |
| Soil or sediment |
≥30 g per tube, 5–8 replicate tubes |
Remove large debris, store at –80°C |
Collect from representative locations |
| Other environmental samples |
Contact for guidelines |
Keep frozen or refrigerated depending on matrix type |
Specify matrix and collection method in manifest |
General Tips:
- Use sterile containers and avoid contamination.
- Provide a manifest with sample IDs, type, and collection details.
- Ship promptly on dry ice to preserve DNA proximity signals.
Real-World Applications — Research Scenarios
Meta-Hi-C / Meta-3C unlocks biological associations that remain hidden in conventional metagenomics, enabling researchers to address diverse scientific questions.
| Research Area |
Example Application |
| Environmental Microbiology |
Linking soil phages to their bacterial hosts to study viral roles in nutrient cycling and ecosystem resilience. |
| Host-Associated Microbiomes |
Mapping plasmid-borne antimicrobial resistance genes in the gut to specific bacterial strains for resistance surveillance. |
| Virome Studies |
Identifying and classifying crAss-like phages and their host range in human or animal gut communities. |
| Agricultural Microbiology |
Tracking horizontal gene transfer events in livestock microbiomes to inform biosecurity and feed additive strategies. |
| Bioprospecting & Synthetic Biology |
Recovering novel biosynthetic gene clusters from uncultivable strains for drug and enzyme discovery. |
By capturing DNA–DNA proximity within intact cells, these methods deliver high-confidence host–MGE networks, allowing for more accurate ecological, evolutionary, and functional interpretations across multiple research contexts.
Case Studies — Meta Hi-C / Meta-3C in Action
Summary:
The OMM12 synthetic bacterial community is a stably maintained, artificially constructed consortium in the mouse gut. This study performed Hi-C experiments on the OMM12 community (12 bacterial strains) under in vitro conditions and Meta Hi-C on fecal samples from Oligo-MM12 mice under in vivo conditions. Hi-C analysis of the 12 non-model bacteria revealed diverse chromosomal architectures. Meta Hi-C analysis of mouse fecal samples showed well-assembled genomes with no cross-contamination between species. Compared to single-strain in vitro Hi-C interaction maps, large-scale diagonal-like structures were preserved in the gut environment, while local structural features differed markedly. These structures remained stable in vivo, likely reflecting growth condition differences imposed by the gut environment and their influence on bacterial physiology.
Hi-C data also revealed 16 functional prophages exhibiting CID-like features, enabling refinement of genomic boundaries and identification of circularization events and activation states. Concurrent virome sequencing showed that 11 of these prophages produced viral particles. A follow-up analysis performed a year later confirmed that functional prophages constitute a persistent phage population within the OMM12 mouse gut.
Bacterial chromosome structure variation and stability in the mouse gut
Why CD Genomics? — Technical Differentiators
Choosing the right partner for Meta-Hi-C / Meta-3C sequencing is not just about data output—it's about data you can trust for high-impact research. At CD Genomics, our approach is optimized for accuracy, reproducibility, and scientific insight.
1. Optimized Experimental Workflows
- Balanced GC Coverage — Our Meta-3C method uses a multi-enzyme digestion strategy to ensure uniform representation across diverse microbial taxa.
- Low Contamination Rates — Proven protocols and contamination-control measures maximize bin purity in high-complexity communities.
- Flexible Input Compatibility — Support for a wide range of environmental and host-associated sample types.
2. High-Confidence Bioinformatics Pipeline
- Proximity-Aware Clustering — Advanced algorithms tailored to Hi-C / 3C datasets for accurate MAG reconstruction.
- MGE–Host Network Mapping — Robust detection and linkage of plasmids, bacteriophages, integrons, and ARGs to specific hosts.
- QC at Every Stage — Comprehensive quality metrics, from raw read assessment to final genome bin validation.
3. Researcher-Focused Data Delivery
- Publication-ready visualizations (host–MGE interaction maps, contact heatmaps).
- Customizable data formats for integration into your existing analysis workflows.
- Detailed reporting that supports both exploratory and hypothesis-driven research.
4. Global Project Support
Our team has experience collaborating with researchers worldwide, adapting project designs to local regulatory and logistical conditions while maintaining rigorous scientific standards.
Deliverables — What You Receive for Immediate Research Use
Clear, actionable outputs to accelerate your microbiome research.
High-Quality MAG Collection
Curated metagenome-assembled genomes (MAGs) with completeness and contamination metrics, fully annotated and organized for seamless downstream analysis.
Verified Host–MGE Association Tables
Confidence-scored links between plasmids, bacteriophages, integrons, antimicrobial resistance genes, and their microbial hosts—enabling precise ecological and functional mapping.
Visualizations & Contact Maps
Publication-ready host–MGE interaction networks, Hi-C/3C contact heatmaps, and binning diagrams—suitable for both in-depth interpretation and clear presentation.
Full Methodology Documentation
A transparent record of experimental protocols, sequencing parameters, and bioinformatics pipelines—ensuring reproducibility and compliance with best-practice standards.
Optional Add-Ons
Custom data formatting (e.g., Excel exports, Cytoscape-ready network files), advanced comparative genomics, or one-on-one review sessions to guide your next experimental phase.
Technical FAQs — Your Questions, Answered
- 1. How does Meta Hi-C / Meta-3C improve metagenome binning compared to shotgun sequencing alone?
- 2. Can this method identify phage–host relationships?
- 3. What is the minimum sequencing depth recommended?
- 4. Is it possible to analyze plasmid–host associations?
- 5. Can you integrate metatranscriptomics or metabolomics data?
- 6. How reproducible is the method across replicates?
