Neighborhood-preserving sampling
Local subcommunities remain grouped before tagging. This retains ecological context that homogenization removes, helping you test whether taxa share a recurring microhabitat.
Spatial Neighborhood Sequencing of Microbial Communities
Bulk 16S sequencing shows which taxa are present, but it cannot reveal which microbes repeatedly occupy the same micron-scale neighborhood or reorganize after a perturbation. CD Genomics provides a custom spatial neighborhood sequencing service that preserves local microbial subcommunities, assigns molecular neighborhood tags, profiles targeted 16S regions with paired-end sequencing and reconstructs taxon co-association patterns. The design is feasibility-gated because specimen structure, particle recovery, barcode balance and community density determine whether local neighborhoods remain interpretable.
Move from community composition to local ecological organization
- Measure many local subcommunities instead of averaging all organisms into one bulk profile.
- Compare neighborhood and bulk abundance so common taxa are not mistaken for specific spatial partners.
- Prioritize recurrent associations and spatial hubs for imaging, isolation or functional follow-up without claiming physical coordinates or causal interaction.
Spatially preserved microbial subcommunities are tagged, sequenced and reconstructed as neighborhood co-association networks.
Resolve Local Microbial Organization beyond a Bulk Average
Spatial neighborhood sequencing asks whether taxa are repeatedly found in the same small subcommunity. It is useful when the biological question concerns local partnerships, exclusion patterns, community hubs or spatial rearrangement after diet, treatment or environmental change.
A preserved specimen is partitioned into many micron-scale neighborhoods. Each neighborhood receives a molecular tag before targeted 16S sequencing, allowing reads from the same local unit to be grouped computationally. The result is a neighborhood-by-taxon matrix that supports co-occurrence testing across thousands of local observations.
This measurement is different from a coordinate-based spatial map. It captures who was near whom within the sampled neighborhood scale, but it does not return an x/y position for every organism. If exact tissue coordinates or direct visualization are required, Microbial FISH Probe Design and Detection is the more appropriate primary method.
Scalable targeted readout
Targeted 16S sequencing measures many neighborhoods in parallel. The larger number of local observations supports association testing that would be impractical by manually imaging every taxon.
Bulk-aware statistics
Matched bulk profiles and prevalence-aware null models separate specific neighborhood enrichment from apparent association caused by high overall abundance.
| Study question | Recommended design | Primary evidence |
|---|---|---|
| Which taxa repeatedly share a local microenvironment? | Neighborhood sequencing with matched bulk 16S profiling | Pairwise enrichment, depletion and recurring assemblages. |
| Does an intervention reorganize the community? | Replicated baseline and post-intervention neighborhood profiles | Changes in association strength, hub membership and neighborhood diversity. |
| Where exactly is a taxon in tissue? | Probe-based imaging rather than neighborhood sequencing alone | Direct spatial coordinates and morphology. |
| What genes and pathways are present? | Microbial Metagenomics | Gene-level and pathway-level community potential. |
The service is planned as a custom research project rather than a fixed kit. During design, we define the biological scale, specimen preservation route, neighborhood recovery controls, taxonomic resolution, replication and decision criteria for expanding beyond the pilot. This converts an emerging research method into a bounded study with explicit evidence and limitations.
Pilot Spatial Preservation before Scaling Neighborhood Counts
The workflow separates method feasibility from biological inference. A pilot first tests whether the specimen can be partitioned without losing local structure and whether neighborhood tags and 16S signals remain balanced enough for comparison.
Define the neighborhood question
Specify matrix, comparison groups, expected community density, desired spatial scale and whether bulk 16S or imaging will provide a reference.
Preserve and partition
Process intact fixed material through a compatible, validated route that retains small microbial subcommunities and includes blank and mixing controls.
Tag and sequence
Assign neighborhood-specific molecular tags, amplify the selected 16S region and use Illumina paired-end sequencing to recover taxon observations per local unit.
Reconstruct associations
Decode tags, build the neighborhood matrix, control for prevalence and technical mixing, and compare spatial associations across groups or time points.
A pilot tests spatial preservation, neighborhood tagging, targeted 16S sequencing and association reconstruction before project expansion.
Illumina paired-end short-read sequencing is used for the targeted 16S readout because it supports scalable processing of many tagged neighborhoods and consistent base-level quality. Sequencing depth is allocated according to the number of retained neighborhoods, expected taxa per neighborhood and barcode balance rather than by applying one fixed read count to every study.
Three checkpoints protect interpretation. First, an intact-material pilot determines whether the matrix can be partitioned reproducibly. Second, negative and artificial-mixing controls reveal background tagging or barcode collision. Third, a matched bulk profile estimates taxon prevalence. Together, these controls reduce the risk that processing artifacts or dominant taxa are reported as biological spatial partners.
The exact sample-processing and partition route is selected after feasibility review to match the specimen matrix, preservation history and intended neighborhood scale. The service therefore focuses on a measurable result: tagged local 16S subcommunities and evidence-graded associations.
Submit Intact Material that Preserves the Original Community Structure
The values below are literature-informed planning targets for feasibility review, not fixed acceptance thresholds. Matrix density, fixation, mucus content and background material can change the required input.
| Input | Preferred amount | Replicates / controls | Important note |
|---|---|---|---|
| Preserved microbiome material | ≥3 mm3 usable material per pilot piece preferred | ≥3 biological replicates per group when feasible | Do not homogenize; document fixation, storage and orientation. |
| Fixed tissue or biofilm block | ≥3 pieces or ≥3 × 3 mm usable area preferred | Matrix blank and handling control | Compatibility depends on matrix permeability and microbial density. |
| Matched bulk community DNA | ≥50 ng total, ≥2 ng/µL preferred | Extraction blank | Used to estimate overall taxon prevalence and support interpretation. |
| Existing tagged 16S libraries or reads | Complete library set and neighborhood map | Blank, mixing and batch controls | Provide tag design, target region, platform and processing history. |
Provide the sample matrix, collection method, fixation or preservation reagent, storage temperature, sample age, previous washing steps, expected bacterial load, study groups and any paired 16S, metagenomic or imaging data. A small pilot aliquot should represent the same handling conditions as the main cohort.
Service boundary: the standard project accepts preserved material or existing molecular data and returns sequence-based neighborhood analysis. It does not require microbial culture and does not return live microorganisms. Fresh clinical diagnostic specimens, absolute tissue-coordinate mapping and host spatial transcriptomics require different workflows.
Turn Tagged Neighborhoods into Evidence-Graded Spatial Associations
Analysis begins with a neighborhood-by-taxon matrix, not a single community profile. Every association is evaluated against barcode quality, neighborhood complexity, overall prevalence and replicate consistency.
Tag decoding and neighborhood quality control
Paired-end reads are filtered, tag combinations are decoded and the targeted 16S region is resolved into amplicon sequence variants or another agreed taxonomic unit. Neighborhoods with insufficient reads, abnormal tag combinations or control-like profiles are excluded using documented thresholds.
Per-neighborhood richness and read balance are inspected alongside blank and artificial-mixing controls. A high apparent richness can indicate a genuinely dense local community, but it can also signal merged particles, tag collision or free-DNA background. Keeping those alternatives visible prevents technical aggregation from being interpreted as a biological hub.
Prevalence-aware association testing
Taxa that are common in the bulk sample will co-occur by chance more often than rare taxa. We therefore compare observed pair frequencies with a fixed-margin permutation or another project-appropriate null model that preserves relevant abundance structure. Empirical significance and multiple-testing control are reported with effect size.
This feature changes the result from a descriptive heat map into testable evidence. A positive association must be stronger than expected from prevalence alone, while a negative association requires adequate opportunity for the pair to have been observed. Sparse taxa remain visible but are not assigned strong ecological conclusions without sufficient support.
Spatial hubs, assemblages and group comparison
Significant associations can be summarized as a taxon network, recurring assemblages or hub membership. Network centrality is treated as a prioritization signal, not proof that a taxon controls the community. When groups or time points are available, we test whether associations, neighborhood diversity or assemblage prevalence shift consistently across replicates.
Longitudinal designs require attention to repeated measures. Subject-aware comparisons can distinguish persistent associations from reversible or intervention-specific changes. For cross-sectional studies, batch, anatomy and sampling depth are reviewed as possible confounders before biological interpretation.
| Analysis output | What it supports | Interpretation boundary |
|---|---|---|
| Neighborhood quality profile | Decides which local units are sufficiently supported for analysis. | Low-quality units are not rescued by pooling. |
| Pairwise association matrix | Identifies enriched or depleted taxon pairs after prevalence control. | Association does not prove direct physical contact or causality. |
| Assemblage and hub summary | Prioritizes recurring local community structures for follow-up. | Hub status depends on sampling scale and taxonomic resolution. |
| Group or time contrast | Tests whether spatial organization changes with an intervention or condition. | Replication and paired design determine inferential strength. |
Barcode quality control and prevalence-aware statistics convert local 16S profiles into evidence-graded neighborhood associations.
Read the Result without Overcalling Interaction
A final result view separates technically supported positive associations, negative associations and unresolved pairs. Links can be ranked by effect size, repeatability and evidence across controls, while uncertain links remain labeled for follow-up rather than being forced into the network.
A neighborhood association network highlights recurrent hubs while retaining unsupported and prevalence-driven pairs as unresolved.
For custom statistics, taxonomic harmonization or integration with other microbial datasets, the project can be extended through Microbial Bioinformatics.
Receive Neighborhood-Level Evidence with Its Quality Context
The report preserves the chain from retained neighborhood to ecological interpretation, allowing technical reviewers to see why an association was accepted, downgraded or excluded.
Neighborhood QC summary
Review retained units, read balance, tag recovery, background signals, richness distribution and control behavior.
Spatial association results
Explore taxon-pair enrichment or depletion, effect sizes, adjusted significance and replicate consistency.
Assemblage comparison
Compare recurring hubs, neighborhood diversity and group- or time-dependent spatial reorganization.
Results may include abundance and prevalence summaries, neighborhood composition tables, association matrices, network views, hub rankings, group contrasts and a methods record. The interpretation distinguishes measured neighborhood co-occurrence from predicted ecological interaction.
Candidate pairs can be prioritized for probe-based imaging, targeted isolation, perturbation assays or longitudinal validation. This ordering helps customers invest follow-up effort in associations that are recurrent and technically supported rather than selecting pairs from bulk correlation alone.
No recovery rate, number of significant links or spatial resolution is guaranteed before the pilot. Those outputs depend on preserved structure, neighborhood count, community density, taxonomic signal and the experimental comparison.
Use Neighborhood Evidence to Prioritize Ecological Mechanisms
Gut-community organization
Ask whether commensals repeatedly occupy shared micron-scale neighborhoods. Association and hub results identify candidate local partnerships for imaging or isolate-based validation.
Intervention response
Compare baseline and post-diet, drug or probiotic neighborhoods. Changes in link strength and assemblage membership reveal reorganization that bulk abundance can miss.
Biofilm and environmental ecology
Profile preserved biofilm, soil aggregate or other structured communities. Recurring local groups help distinguish habitat-linked assemblages from whole-sample correlation.
Neighborhood sequencing is particularly useful when a community remains compositionally similar but its local arrangement may have changed. In that setting, bulk diversity metrics can look stable while new partnerships form or old hubs dissolve. Local evidence supplies a mechanistic hypothesis that can guide the next experiment.
It can also refine candidate selection. Instead of attempting to validate every correlation from a bulk network, customers can prioritize pairs that recur across many neighborhoods, survive prevalence-aware testing and change coherently with the study condition. The method narrows the search space; it does not replace direct imaging or functional validation.
Spatial neighborhood sequencing supports gut ecology, intervention studies and structured environmental microbiome research.
Case Study: Spatial Assemblages Reveal Microbiome Responses to Dietary Perturbation
Source: Uppal, G., Urtecho, G., Richardson, M. et al. MCSPACE: inferring microbiome spatiotemporal dynamics from high-throughput co-localization data. Microbiome 14, 28 (2026).
The investigators asked how microbial spatial assemblages persist or reorganize over time and whether high-throughput co-localization data can separate stable community structure from diet-responsive changes.
The study analyzed sequencing-based microbial co-localization data from longitudinal mouse and human gut datasets. Neighborhood observations were modeled as latent spatial assemblages, then compared across subjects, time points and dietary perturbations.
The analysis recovered spatially coherent assemblages with both persistent and dynamic behavior. In the mouse experiment, serial sampling across dietary conditions revealed assemblages that shifted with diet while others remained comparatively stable, adding spatial organization to ordinary abundance trends.
Longitudinal neighborhood profiles separate persistent microbial assemblages from diet-responsive spatial reorganization.
High-throughput neighborhood sequencing and model-based analysis provided a way to follow microbial spatial structure over time. The work shows why repeated local observations can reveal intervention-responsive organization that a single bulk composition profile cannot resolve.
Choose the Method that Matches the Spatial Question
Best suited to: intact, preserved microbial communities where the primary question concerns recurring local co-association, neighborhood hubs or spatial reorganization across replicated conditions.
| Goal | Recommended method | Why |
|---|---|---|
| Discover recurring local taxon associations at scale | Spatial neighborhood sequencing | Profiles many tagged local subcommunities with a targeted sequencing readout. |
| Locate known taxa at exact tissue coordinates | Multiplex FISH or other imaging | Preserves morphology and direct position for selected targets. |
| Measure whole-community composition or functional genes | Bulk 16S or metagenomic sequencing | More efficient when local organization is not the question. |
| Measure host gene expression with spatial coordinates | Host–microbiome spatial transcriptomic design | Addresses a different molecular layer and requires matrix-specific validation. |
When another approach is more suitable: choose FISH if the decision depends on exact location, morphology or direct visualization of a small target set. Choose bulk Microbial Diversity Analysis when the goal is primarily taxonomic composition. Neighborhood sequencing is not a substitute for direct contact imaging, culture-based interaction tests or causal perturbation.
For a feasibility review, provide sample matrix and preservation, expected microbial density, study groups, replicate count, desired neighborhood scale, whether exact coordinates are required, available bulk 16S or metagenomic data, and the biological decision the spatial evidence should support.
Frequently Asked Questions
No. The standard result identifies taxa that share the same recovered micron-scale neighborhood. Exact x/y coordinates require an imaging or coordinate-preserving spatial method.
No. The core readout is targeted 16S sequencing of tagged neighborhoods. Whole-metagenome functional profiling is a separate service and should not be assumed from this page.
No. It shows repeated co-localization above the null expectation at the sampled scale. Imaging, isolation or perturbation is needed to test direct interaction and mechanism.
Potentially. Fixation chemistry, storage time, structure retention and 16S accessibility must be evaluated in a pilot before the full cohort is committed.
The number depends on community complexity, barcode retention, taxon prevalence, replication and the expected biological effect. Pilot data are used to set the expansion target.
References
- Richardson, M. et al. SAMPL-seq reveals micron-scale spatial hubs in the human gut microbiome. Nature Microbiology 10, 527–540 (2025).
- Uppal, G. et al. MCSPACE: inferring microbiome spatiotemporal dynamics from high-throughput co-localization data. Microbiome 14, 28 (2026).
- Sheth, R. U. et al. Spatial metagenomic characterization of microbial biogeography in the gut. Nature Biotechnology 37, 877–883 (2019).
- Lötstedt, B. et al. Spatial host–microbiome sequencing reveals niches in the mouse gut. Nature Biotechnology 42, 1394–1403 (2024).
- Cao, B. et al. Spatial profiling of microbial communities by sequential FISH with error-robust encoding. Nature Communications 14, 1477 (2023).
For research use only. Not for clinical diagnosis, treatment or individual health assessment.
* For research purposes only, not intended for clinical diagnosis, treatment, or individual health assessments.
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