Biology subjects

De Vlaminck, I.

Publications and source records attributed to De Vlaminck, I..

At least 19 recordsLinked to original sources

bioRxiv2026

MHC-I downregulation is associated with immune-evasion in breast cancers with heterogeneous activation of epithelial-mesenchymal plasticity

Cancer cell-intrinsic epithelial-mesenchymal plasticity (EMP) drives carcinoma progression through increased intratumoral heterogeneity and an immunosuppressive tumor microenvironment (TME). Specifically, EMP activation in murine mammary carcinomas results in exclusion of CD8+ T-cells and recruitment of immunosuppressive M2-like macrophages, resulting in resistance to anti-CTLA-4 immune checkpoint blockade (ICB) therapy. Notably, mixed E-qM tumors in which only 10% of cancer cells have activated EMP are resistant anti-CTLA-4 immune checkpoint blockade (ICB) therapy. This suggests that minority fractions of qM cancer cells could, in theory, exert immunosuppressive effects on surrounding E cancer and immune cells to shield the entire heterogeneous tumor against immune attack. However, this has not yet been demonstrated. Here, we use spatial transcriptomic profiling to demonstrate that mixed E-qM tumors assemble immunosuppressive cellular niches. Furthermore, E cancer cells within mixed E-qM tumors experience long-term MHC-I downregulation leading to resistance to elimination by CD8+ T-cells. This is associated with the exclusion of T-cells from the tumor core and a dysfunctional phenotype in the remaining CD8+ T-cells. qM cancer cells recruit immunosuppressive M2-like macrophages to mixed tumors, which further downregulates E cancer cell-intrinsic MHC-I levels. Finally, we demonstrate that human triple-negative breast cancers with increased EMP activation exclude T-cells from the tumor core. Together, these findings reveal that qM cancer cells modulate the immune infiltrate of mixed tumors, promoting MHC-I downregulation and evasion of immunological control by CD8+ T-cells.

cancer biology↗

bioRxiv2026

High-resolution spatial transcriptomics maps viral tropism and reveals spatially organized immune modules in viral encephalitis

Viral encephalitis is a debilitating disease that most commonly affects vulnerable populations, including the very young and elderly. Despite its severity, few countermeasures exist due to the structural and immunological complexities of the central nervous system (CNS). To better understand the spatial dynamics of viral spread and the concurrent host immune responses, we used high-resolution spatial transcriptomics to profile reovirus infection in the neonatal mouse brain at 3, 5, and 7 days post-infection. We constructed a comprehensive spatiotemporal atlas of infection, which revealed viral dissemination from sites of cerebrospinal fluid circulation to neighboring brain parenchyma, with enriched infection in the thalamus and midbrain coincident with Slc17a6 (VGLUT2) excitatory neurons. Unbiased spatial gene co-expression network analysis uncovered rich gene lists linked to temporal waves of host immune responses, originating with interferon-stimulated gene modules, followed by myeloid cell infiltration and adaptive cytotoxic T-cell responses at times of peak disease. Furthermore, we identified spatial correlation between viral transcripts and several upregulated host snoRNA-related genes (e.g., Nop58 and Snhg1) with high-confidence, suggesting viral use of host ribosomal modification machinery. We also observed a strong anti-correlation of astrocyte markers with reovirus transcripts, suggesting glial cell disruption. This work provides a high-definition spatial framework to understand interactions between viral infection and host immunity in the brain.

microbiology↗

bioRxiv2026

A NON-CANONICAL ROLE FOR NOTCH3 IN BUILDING THE INTESTINAL LYMPHATIC NICHE

Lymphatic dysfunction drives severe and often intractable human diseases, yet the cellular mechanisms that establish functional lymphatic vasculature remain poorly understood. In the intestine, lacteals are specialized lymphatic vessels that absorb dietary lipids and rely on surrounding villus smooth muscle to propel lymph, forming the muscular-lacteal complex (MLC). How distinct mesenchymal populations coordinate assembly of this functional lymphatic unit remains unknown. By integrating developmental single-cell profiling, genetic lineage tracing, conditional mouse genetics, and functional assays of lipid absorption, we identify Notch3 as a central organizer of MLC development that coordinates communication between distinct mesenchymal lineages. While Notch3 promotes smooth muscle differentiation within the PDGFR lineage, PDGFR{beta} lineage cells do not directly contribute to villus smooth muscle. Instead, they function as Notch3-dependent signaling hubs that instruct expansion and differentiation of neighboring PDGFR smooth muscle progenitors via paracrine TGF{beta} signaling. Loss of Notch3 in PDGFR{beta} cells disrupts MLC development, impairs intestinal lipid absorption, and causes postnatal growth failure and lethality. Restoration of TGF{beta} signaling rescues the structural, functional, and survival defects caused by Notch3 loss, identifying TGF{beta} as a critical downstream effector of the Notch3 pathway. Furthermore, selective inhibition of canonical Notch signaling in the PDGFR{beta} lineage fails to phenocopy Notch3 deletion, revealing a non-canonical mechanism of Notch3 function in intestinal mesenchymal development. Together, these findings establish PDGFR{beta} cells as essential mesenchymal signaling organizers and define a new paradigm in which lineage-specific, non-canonical Notch3 signaling coordinates villus stromal communication to build a functional intestinal lymphatic niche.

developmental biology↗

bioRxiv2026

High-resolution temporal profiling reveals synchronized dynamics of the mouse gut microbiome

The gut microbiome is a highly dynamic ecosystem, yet its temporal organization remains poorly understood because microbiome sampling is typically limited to sparse time points. To overcome this challenge, we developed an automated device to enable continuous fecal sampling from individual mice at minute-to hour-scale resolution. Combining full-length 16S rRNA amplicon sequencing with a limited set of long-read metagenomic references, we economically reconstructed genome- and function-level trajectories at high temporal resolution. Automated hourly sampling over 14 consecutive days enabled phase analysis, revealing collective synchronization of taxa partitioned by carbohydrate utilization strategies between day and night, with microbial taxa and functional genes showing reproducible temporal succession across mice. Perturbations such as cage transfer or antibiotic treatment transiently disrupted this functional synchronization, followed by recovery toward a coherent dynamical state. This system and analytic frameworks will enable us to explore rapid microbiome dynamics in health and disease.

microbiology↗

bioRxiv2026

Neuroepithelial reprogramming and ERBB vulnerability in canine acanthomatous ameloblastoma

Canine acanthomatous ameloblastoma (CAA) is a locally invasive benign oral neoplasm that is difficult to distinguish from canine oral squamous cell carcinoma (COSCC) due to overlapping clinical, radiologic, and histologic features. Although both tumors exhibit MAPK pathway activation, their mutational landscapes are distinct. Furthermore, previous studies using bulk RNA sequencing (RNA-seq) have demonstrated pronounced differences in programs related to, among others, hypoxia, PI3K-AKT signaling, and cell proliferation. However, these bulk studies lacked the resolution to elucidate the cellular heterogeneity of CAA relative to COSCC. We therefore performed single-nucleus RNA-seq to define the cellular gene expression landscape of CAA, COSCC, and healthy gingiva. Across [~]205,000 nuclei, we identified major epithelial, immune, endothelial, and mesenchymal populations, as well as two epithelial subtypes uniquely enriched in CAA. The CAA-specific keratinocytes exhibited a neuronal-like expression program defined by synaptic regulators, KRAS-associated signaling pathways, and markedly elevated expression of PEG3, ERBB4, GABRB1, MAGI2, and CASK. These findings were validated by bulk RNA-seq, qPCR, and immunohistochemistry, which demonstrated strong nuclear localization of PEG3 exclusively in CAA epithelium. A kinase inhibitor screen independently identified ERBB4 as a candidate therapeutic vulnerability, and pharmacologic inhibition with neratinib was effective. Together, these findings reveal a previously unrecognized neuroepithelial cell state that defines CAA, distinguishes it from COSCC, and reveals unique diagnostic and therapeutic signaling dependencies. Given the molecular and histopathologic parallels between CAA and human ameloblastoma, these data further position CAA as a naturally occurring comparative model for studying ameloblastoma biology and therapeutic vulnerabilities. Significance StatementCanine acanthomatous ameloblastoma (CAA) is a common locally aggressive oral neoplasm often misdiagnosed as canine oral squamous cell carcinoma (COSCC) due to overlapping clinical, radiologic, and histologic features. Using single-nucleus RNA sequencing of CAA, COSCC, and healthy gingiva, we resolve the microenvironment of these tumors and detect two epithelial subpopulations unique to CAA. These CAA-specific keratinocytes exhibit a neuroepithelial-like signature characterized by synaptic regulators, KRAS-associated signaling, and elevated PEG3 and ERBB4 expression. Functional kinase inhibitor screening of patient derived microtumor slices independently converged on ERBB4 as an effective therapeutic target. Together, our study provides a molecular framework for distinguishing CAA from COSCC and establishes a comparative oncology model with translational relevance to human ameloblastoma and other ERBB-driven epithelial neoplasms.

cancer biology↗

bioRxiv2025

Spatiotemporal Atlas of Heart Development Reveals Blood-Flow-Dependent Cellular, Structural, Metabolic, and Spatial Remodeling

Embryonic heart development depends on coordinated interactions between cellular programs, molecular signaling, and biomechanical forces, yet how mechanical cues shape cellular and molecular pathways remains incompletely understood. We perturbed cardiac blood flow by partial left or right atrial ligation (LAL/RAL) in chick embryos, generating chamber-specific hemodynamic gain- or loss-of-function states. Using single-cell and unbiased, high-resolution spatial transcriptomics, we generated a spatiotemporal atlas of flow-dependent tissue development, enabling systematic investigations of bidirectional interactions between blood-flow mechanics and tissue development. Spatially resolved analyses recapitulated key features of normal morphogenesis including regional maturation and the cellular neighborhood. We further revealed flow-specific remodeling across molecular, cellular, and architectural levels. Altered flow induced LOX-expressing cardiomyocyte and endocardial states, disrupted ventricular layer organization, and delayed maturation, alongside transient metabolic and ion-transport adaptations. Together, these findings define how redistributed blood flow reshapes developing cardiac tissues and provide a framework for studying flow-dependent remodeling in morphogenesis and malformation.

developmental biology↗

bioRxiv2025

Spatial Transcriptomics Identify T Cell-Driven Mechanisms of Kidney Damage in Immune Checkpoint Inhibitor-Associated Acute Interstitial Nephritis

IntroductionImmune checkpoint inhibitor-associated acute interstitial nephritis (ICI-AIN) is the most common finding on histopathology among patients with ICI-associated acute kidney injury (ICI-AKI). Patients with ICI-AIN often have T cell-dominant infiltration of the kidney and high tissue levels of CXCR3 ligands like CXCL9, 10, and 11; however, the mechanisms of inflammation in ICI-AIN are not well-understood. MethodsWe applied a sub-cellular spatial transcriptomics platform (Xenium Prime 5K) to compare the cellular composition of kidney biopsy tissue from patients with ICI-AIN with ICI-treated patients with acute tubular necrosis (ICI-ATN). ResultsAcross 8 kidney biopsy specimens (4 with ICI-AIN, 4 with ICI-ATN), we analyzed 332,000 cells, comprising kidney parenchymal cells and infiltrating immune cells. Using a spatially-aware cellular neighborhood-based classification, we identified cellular niches corresponding to each part of the nephron, in addition to unique fibrotic and inflammatory niches. Gene pathway analysis identified interferon-gamma (IFN-{gamma})/STAT1 signaling as strongly increased in ICI-AIN compared to ICI-ATN. While all inflammatory niches were overrepresented in ICI-AIN, CD8+ T cell infiltration and proinflammatory myeloid cells were the dominant immune niches. Spatial niche crosstalk analysis revealed that CD8+ T cell-derived IFN-{gamma} likely induced a proinflammatory program in myeloid cells, with increased production of CXCL9, 10, and 11. Furthermore, IFN-{gamma} signaling in ICI-AIN was associated with reduced oxidative phosphorylation in kidney tubular niches. ConclusionsSpatial transcriptomics reveal novel insights into key differences in the pathophysiology of ICI-AIN versus ICI-ATN. IFN-{gamma}-producing CD8+ T cells are likely key drivers of ICI-AIN and should be investigated as future therapeutic targets. Translational StatementSpatial transcriptomics may provide insight into differences in the cellular and spatial composition of immune checkpoint inhibitor-associated acute interstitial nephritis (ICI-AIN) and ICI-associated acute tubular necrosis (ICI-ATN). Using the novel Xenium 5K platform, we demonstrate that IFN-{gamma}-producing CD8+ T cells are central to the pathogenesis of ICI-AIN, and that CD8+ T cell-derived IFN-{gamma} likely induces a proinflammatory state in myeloid cells, with increased tissue production of CXCL9, 10, and 11. We then show that a reduction in oxidative phosphorylation and an IFN-{gamma}-driven influx of proinflammatory myeloid cells may further drive kidney damage in ICI-AIN. Many of these pathways represent potential druggable targets, and our findings may therefore inform future therapeutic approaches for ICI-AIN.

immunology↗

bioRxiv2025

Epithelial-Mesenchymal Plasticity is Associated with Immunosuppressive Features in Canine Mammary Carcinomas

Epithelial-mesenchymal plasticity (EMP) is a cellular process activated in carcinoma cells to drive invasiveness, metastasis, and chemoresistance. Recently, we have demonstrated that activation of the EMP program also results in the assembly of an immunosuppressive tumor microenvironment and resistance to immunotherapy in an immunocompetent orthotopic murine model. However, it has yet to be shown whether these findings can be translated to canine carcinomas. Here, we show that in spontaneous canine mammary carcinomas (CMCs), which share similar histopathologic, molecular, and clinical features with human breast cancers, EMP activation is linked to the recruitment of immunosuppressive cells including regulatory T-cells and M2-like macrophages. Additionally, through transcriptomic profiling of CMCs, we identify that the glycoprotein CD109 is associated with EMP-mediated immunosuppression across canine, murine, and human breast cancer models. CD109 has been previously associated with tumorigenicity, but not immunosuppression in cancers of any species. Finally, we identified upregulation of several immunosuppressive paracrine factors across multiple canine carcinomas, including oral squamous cell carcinoma, urothelial carcinoma, and pulmonary carcinoma samples. These findings demonstrate for the first time that the EMP program is associated with immunosuppression in canine carcinomas, with direct translational implications for human breast cancers.

cancer biology↗

bioRxiv2025

Benchmarking large language models for cell-free RNA diagnostic biomarker discovery

Large-language models (LLMs) can parse vast amounts of data and generate executable code, positioning them as promising tools for the development of biomarkers and classifiers from high-throughput omics data. Here, we benchmarked six LLMs, OpenAIs o3 and GPT-4o, Anthropics Claude Opus 4 and Claude 3.7 Sonnet, and Googles Gemini 2.5 Pro and Gemini 2.0 Flash, for disease classification based on plasma cell-free RNA (cfRNA) profiles obtained by RNA sequencing. We analyzed data from cohorts of children with Kawasaki disease (KD) or multisystem inflammatory syndrome in children (MIS-C), adults with active tuberculosis (TB) or other non-TB respiratory conditions, and individuals with myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) or sedentary lifestyle. We assessed two tasks: (i) gene-panel design, where each LLM mined public knowledge to nominate diagnostic genes for use in machine learning (ML), and (ii) end-to-end modeling, where LLMs built an ML workflow directly from raw RNA-seq counts. In the first task, the LLM-derived panels captured canonical immune pathways and outperformed randomly selected genes in all cohorts. They underperformed panels chosen by differential gene expression (DGE) analysis in the KD vs. MIS-C and ME/CFS cohorts but performed comparably or better for the TB cohort. In the second task, o3 produced classifiers for KD vs. MIS-C that performed just as well as conventional statistical methods without human intervention. Performance for TB and ME/CFS cohorts was slightly lower than the conventional approach. These findings delineate current capabilities and limitations of LLMs in diagnostics and open a path for their future use in biomarker discovery.

bioinformatics↗

bioRxiv2025

Minimal Correlation but Complementary Diagnostic Utility for Plasma Cell-free RNA and Proteins

Proteins and RNA circulate in plasma and can offer insights into human physiology. Yet, despite their clinical importance, direct comparisons between these analytes remain unexplored. Here, we measured and compared plasma cell-free RNA (cfRNA) and protein levels for 263 children diagnosed with inflammatory diseases by RNA-sequencing (n=155) and SomaScan proteomics (n=171). Remarkably, cfRNA and protein levels were largely uncorrelated across samples (feature-by-sample r=0.052; median feature-level r=0.009). Nonetheless, machine learning models based on either modality distinguished Kawasaki Disease (KD) from Multisystem Inflammatory Syndrome in Children (MIS-C) with similar high accuracy (median AUC > 0.93). Analysis of KD subtypes revealed distinct cfRNA and protein signatures, with one group showing molecular similarity to MIS-C. These findings underscore the complementary nature of cfRNA and protein profiling and highlight the utility of integrating multiple blood analytes to improve disease classification and deepen our understanding of complex inflammatory conditions.

genomics↗

bioRxiv2025

Measuring Longitudinal Genome-wide Clonal Evolution of Pediatric Acute Lymphoblastic Leukemia at Single-Cell Resolution

Approximately 15-20% of children with acute lymphoblastic leukemia (pALL) are not cured despite years of treatment with more than ten chemotherapeutic agents, yet bulk sequencing reveals minimal somatic variation that could explain genetic treatment resistance. Using error-corrected bulk sequencing, and primary template-directed amplification (PTA)-enabled single-cell exome and whole-genome sequencing, we discovered much more genetic diversity in pALL. Individual leukemic cells harbor 3.7-fold more mutations (mean 3,553) than detected in bulk samples (mean 965). Many ETV6-RUNX1 patients harbor multiple independent ras-mutated clones, and we also identified convergent evolution of JAK2 mutations as well as copy number alterations. PTA-based phylogenetic analysis of over 150 single-cell genomes linked heritable phenotypes to specific genetic alterations and identified low-frequency clones harboring mutations in treatment resistance-associated genes (ITGA9, NTRK3, SULF2) that increased in frequency during treatment. These findings reveal extensive hidden genetic diversity in pALL while providing a framework for the early detection of high-risk leukemic populations.

cancer biology↗

bioRxiv2025

Smoothie: Efficient Inference of Spatial Co-expression Networks from Denoised Spatial Transcriptomics Data

Finding correlations in spatial gene expression is fundamental in spatial transcriptomics, as co-expressed genes within a tissue are linked by regulation, function, pathway, or cell type. Yet, sparsity and noise in spatial transcriptomics data pose significant analytical challenges. Here, we introduce Smoothie, a method that denoises spatial transcriptomics data with Gaussian smoothing and constructs and integrates genome-wide co-expression networks. Utilizing implicit and explicit parallelization, Smoothie scales to datasets exceeding 100 million spatially resolved spots with fast run times and low memory usage. We demonstrate how co-expression networks measured by Smoothie enable precise gene module detection, functional annotation of uncharacterized genes, linkage of gene expression to genome architecture, and multi-sample comparisons to assess stable or dynamic gene expression patterns across tissues, conditions, and time points. Overall, Smoothie provides a scalable and versatile framework for extracting deep biological insights from high-resolution spatial transcriptomics data.

genomics↗

bioRxiv2025

A Temporal and Spatial Atlas of Adaptive Immune Responses in the Lymph Node Following Viral Infection

The spatial organization of adaptive immune cells within lymph nodes is critical for understanding immune responses during infection and disease. Here, we introduce AIR-SPACE, an integrative approach that combines high-resolution spatial transcriptomics with paired, high-fidelity long-read sequencing of T and B cell receptors. This method enables the simultaneous analysis of cellular transcriptomes and adaptive immune receptor (AIR) repertoires within their native spatial context. We applied AIR-SPACE to mouse popliteal lymph nodes at five distinct time points after Vaccinia virus footpad infection and constructed a comprehensive map of the developing adaptive immune response. Our analysis revealed heterogeneous activation niches, characterized by Interferon-gamma (IFN-{gamma}) production, during the early stages of infection. At later stages, we delineated sub-anatomical structures within the germinal center (GC) and observed evidence that antibody-producing plasma cells differentiate and exit the GC through the dark zone. Furthermore, by combining clonotype data with spatial lineage tracing, we demonstrate that B cell clones are shared among multiple GCs within the same lymph node, reinforcing the concept of a dynamic, interconnected network of GCs. Overall, our study demonstrates how AIR-SPACE can be used to gain insight into the spatial dynamics of infection responses within lymphoid organs.

immunology↗

bioRxiv2024

High Resolution Spatial Mapping of Microbiome-Host Interactions via in situ Polyadenylation and Spatial RNA Sequencing

Inter-microbial and host-microbial interactions are thought to be critical for the functioning of the gut microbiome, but few tools are available to measure these interactions. Here, we report a method for unbiased spatial sampling of microbiome-host interactions in the gut at one micron resolution. This method combines enzymatic in situ polyadenylation of both bacterial and host RNA with spatial RNA-sequencing. Application of this method in a mouse model of intestinal neoplasia revealed the biogeography of the mouse gut microbiome as function of location in the intestine, frequent strong inter-microbial interactions at short length scales, shaping of local microbiome niches by the host, and tumor-associated changes in the architecture of the host-microbiome interface. This method is compatible with broadly available commercial platforms for spatial RNA-sequencing, and can therefore be readily adopted to broadly study the role of short-range, bidirectional host-microbe interactions in microbiome health and disease.

genomics↗

bioRxiv2024

Microscale Spatial Dysbiosis in Oral biofilms Associated with Disease

Microbiome dysbiosis has largely been defined using compositional analysis of metagenomic sequencing data; however, differences in the spatial arrangement of bacteria between healthy and diseased microbiomes remain largely unexplored. In this study, we measured the spatial arrangement of bacteria in dental implant biofilms from patients with healthy implants, peri-implant mucositis, or peri-implantitis, an oral microbiome-associated inflammatory disease. We discovered that peri-implant biofilms from patients with mild forms of the disease were characterized by large single-genus patches of bacteria, while biofilms from healthy sites were more complex, mixed structures. Based on these findings, we propose a model of peri-implant dysbiosis where changes in biofilm spatial architecture allow the colonization of new community members. This model indicates that spatial structure could be used as a potential biomarker for community stability and has implications in diagnosis and treatment of peri-implant diseases. These results enhance our understanding of peri-implant disease pathogenesis and may be broadly relevant for spatially structured microbiomes.

microbiology↗

bioRxiv2024

Bone mineral density affects tumor growth by shaping microenvironmental heterogeneity

Breast cancer bone metastasis is the leading cause of mortality in patients with advanced breast cancer. Although decreased mineral density is a known risk factor for bone metastasis, the underlying mechanisms remain poorly understood because studying the isolated effect of bone mineral density on tumor heterogeneity is challenging with conventional approaches. Here, we investigate how bone mineral content affects tumor growth and microenvironmental complexity in vivo by combining single-cell RNA-sequencing with mineral-containing or mineral-free decellularized bone matrices. We discover that the absence of bone mineral significantly influences fibroblast and immune cell heterogeneity, promoting phenotypes that increase tumor growth and alter the response to injury or disease. Importantly, we observe that the stromal response to matrix mineral content depends on host immunocompetence and the murine tumor model used. Collectively, our findings suggest that bone mineral density affects tumor growth by altering microenvironmental complexity in an organism-dependent manner.

bioengineering↗

bioRxiv2023

A Spatiotemporal Molecular Atlas of the Ovulating Mouse Ovary

Ovulation is essential for reproductive success, yet the underlying cellular and molecular mechanisms are far from clear. Here, we applied high-resolution spatiotemporal transcriptomics to map out cell-type- and ovulation-stage-specific molecular programs as function of time during follicle maturation and ovulation in mice. Our analysis revealed dynamic molecular transitions within granulosa cell types that occur in tight coordination with mesenchymal cell proliferation. We identified new molecular markers for the emerging cumulus cell fate during the preantral-to-antral transition. We describe transcriptional programs that respond rapidly to ovulation stimulation and those associated with follicle rupture, highlighting the prominent roles of apoptotic and metabolic pathways during the final stages of follicle maturation. We further report stage-specific oocyte-cumulus cell interactions and diverging molecular differentiation in follicles approaching ovulation. Collectively, this study provides insights into the cellular and molecular processes that regulate mouse ovarian follicle maturation and ovulation with important implications for advancing therapeutic strategies in reproductive medicine.

genomics↗

bioRxiv2023

Spatial Mapping of Mobile Genetic Elements and their Cognate Hosts in Complex Microbiomes

The frequent exchange of mobile genetic elements (MGEs) between bacteria accelerates the spread of functional traits, including antimicrobial resistance, within the human microbiome. Yet, progress in understanding these intricate processes has been hindered by the lack of tools to map the spatial spread of MGEs in complex microbial communities, and to associate MGEs to their bacterial hosts. To overcome this challenge, we present an imaging approach that pairs single molecule DNA Fluorescence In Situ Hybridization (FISH) with multiplexed ribosomal RNA FISH, thereby enabling the simultaneous visualization of both MGEs and host bacterial taxa. We used this methodology to spatially map bacteriophage and antimicrobial resistance (AMR) plasmids in human oral biofilms, and we studied the heterogeneity in their spatial distributions and demonstrated the ability to identify their host taxa. Our data revealed distinct clusters of both AMR plasmids and prophage, coinciding with densely packed regions of host bacteria in the biofilm. These results suggest the existence of specialized niches that maintain MGEs within the community, possibly acting as local hotspots for horizontal gene transfer. The methods introduced here can help advance the study of MGE ecology and address pressing questions regarding antimicrobial resistance and phage therapy.

microbiology↗