Biology subjects

McIlwain, D. R.

Publications and source records attributed to McIlwain, D. R..

11 recordsLinked to original sources

bioRxiv2026

Quantum Barcoding Bridges High-Dimensional Immune Phenotyping with Signaling Responses across Species

Cross-species immune profiling is limited by marker-panel size and antibody cross-reactivity. We benchmark Quantum Barcoding (QBC), a split-pool oligo-antibody assay, against mass cytometry in human and rhesus macaque blood and integrate separately measured cells using MARIO. The resulting computationally matched profiles carry 174 protein features. Population-frequency concordance was higher in humans (Pearson r = 0.92) than rhesus macaques (r = 0.55), and fusion resolved complementary lineage subsets. Unstimulated signaling conservation varied by lineage, with B-cell profiles correlated across species (Spearman {rho} = 0.70). In the primary PBMC-reference analysis, GM-CSF increased pSTAT5 in human monocytes and dendritic populations and rhesus dendritic cells. Network inference identified convergent pSTAT5-centered connectivity changes in human monocytes and rhesus dendritic cells, including pSTAT1-edge reversal and gained pSTAT3/pERK coupling. These results connect broad surface phenotypes to inferred signaling organization while retaining species- and population-specific differences.

systems biology↗

bioRxiv2026

Coordinated immune-epithelial dynamics in the nasal epithelium protect against respiratory virus infection

Epithelial remodeling is a hallmark of host antiviral responses that strengthen barrier defenses against infection. Our current understanding of viral pathophysiology within the nasal epithelium, the initial site of most respiratory viral infections, remains incomplete due to limited understanding of the native tissue architecture and protective epithelial remodeling during immune events. Leveraging coronavirus disease 2019 (COVID-19) as a model, we applied spatial multi-omics on nasal cross-sectional tissues to characterize the immune-epithelial landscape during infection, identifying a coordinated increase in goblet cells and suppressive macrophages associated with elevated IL13 in the immune compartment. Our results further reveal that goblet cell and suppressive macrophage enrichment are spatially linked in proximity to IL13-expressing CD4 T cells, consistent with IL13-driven remodeling in situ. Using a primary human nasal air-liquid interface model, we demonstrate that IL13 alone is sufficient to remodel epithelial composition and morphology, subsequently restricting viral infection by reshaping the apical mucus barrier of the nasal epithelium. Our findings uncover a spatially organized, IL13-driven circuit for immune-epithelial remodeling as a protective barrier against respiratory viral infections.

immunology↗

bioRxiv2025

Fluid-Squid: DIY Multiplexed Imaging of Cells and Tissues

Recent advances in multiplexed single-cell characterization have revolutionized our insight into cell biology, but many available technologies remain limited by high costs or a lack of customizability. To address these challenges, we developed Fluid-Squid, a cost-effective, quantitative imaging platform that integrates automated fluidics to support customizable, do-it-yourself multiplexed imaging workflows. Using Fluid-Squid, we successfully imaged fresh frozen human intestinal tissues with a 36-plex oligonucleotide-barcoded antibody panel and further demonstrated the feasibility of lyophilizing such multiplexed panels. We also adapted existing multiplexed imaging workflows to characterize individual cells to identify immune cell populations, phenotype, and antigen-specific cells from mouse splenocytes and human peripheral blood mononuclear cells (PBMCs) with a 39-antibody panel. To further expand its utility, we developed a barcoding strategy that allows for the pooling and simultaneous staining of multiple samples, reducing time, costs, and batch effects in single-cell experiments. This approach facilitated rapid titration to optimize antibody concentrations and assess the impact of various blood preparation methods on cell type retention. Overall, our work provides a new open-source framework for automated fluidics and microscopy in a flexible, cost-effective platform, empowering adaptable multiplexed characterization of both single cells and tissues.

bioengineering↗

bioRxiv2025

PASTA: Versatile Tyramine-oligonucleotide Amplification for Multi-modal Spatial Biology

Spatial proteomics techniques have revolutionized our understanding of tissue architecture, but are frequently limited by detection sensitivity, bioconjugation limitations, multiplexing capacity, and multi-modal integration. Here we present Protein and nucleic Acid Serial Tyramine Amplification (PASTA), a novel signal amplification approach that significantly enhances detection sensitivity while maintaining compatibility with diverse spatial profiling methodologies. PASTA utilizes horseradish peroxidase (HRP) recruitment pathways to generate tyramine radicals that deposit oligonucleotides, enabling adaptable signal amplification across multiple biomarkers at high-plex via cyclical imaging using complementary fluorophore-labeled oligonucleotides. We demonstrate that PASTA achieves up to 100-fold signal enhancement for markers with minimal background in blank controls. The method is compatible with in situ hybridization for DNA/RNA detection, proximity ligation assays for protein-protein interactions, sequential antibody staining protocols, or any modular combination thereof. PASTA enables antibody rescue of markers with suboptimal signal-to-noise ratios and is versatile in its applications to unconjugated antibodies, and multi-round probe-based RNA detection systems beyond current capabilities. This technique addresses key limitations in spatial-omics by enhancing sensitivity for challenging targets while maintaining compatibility with established multiplexing strategies, providing a versatile, cost-efficient, and valuable tool for comprehensive spatial tissue analysis in both research and clinical applications.

molecular biology↗

bioRxiv2024

The effect of circulating neutralizing antibodies on the replication of SARS-CoV-2 variants following post-vaccination infections.

The impact of pre-existing neutralizing antibodies (NAbs) titers on SARS-CoV-2 viral shedding dynamics in post-vaccination infection (PVI) are not well understood. We characterized viral shedding longitudinally in nasal specimens in relation to baseline (pre/peri-infection) serum neutralizing antibody titers in 125 participants infected with distinct SARS-CoV-2 variants. Among 68 participants who had received vaccinations, we quantified the effect of baseline serum NAb titers on maximum viral RNA titers and on the duration of infectivity. Baseline NAb titers were higher and efficiently targeted a broader range of variants in participants who received one or two monovalent ancestral booster vaccinations compared to those with a full primary vaccine series. In participants with Delta variant infections, baseline NAb titers targeting Delta were negatively correlated with maximum viral RNA copies. Per log10 increase in baseline NAb IC50, maximum viral load was reduced -2.43 (95% confidence interval [CI] -3.76, -1.11) log10 N copies and days of infectious viral shedding were reduced -2.79 [95% CI: -4.99, -0.60] days. By contrast, in those with Omicron infections (BA.1, BA.2, BA.4 or BA.5 lineages) baseline NAb responses against Omicron lineages did not predict viral outcomes. Our results provide robust estimates of the effect of baseline NAbs on the magnitude and duration of nasal viral replication after PVI (albeit with an unclear effect on transmission) and show how immune escape variants efficiently evade these modulating effects.

immunology↗

bioRxiv2021

Robust Single-cell Matching and Multi-modalAnalysis Using Shared and Distinct FeaturesReveals Orchestrated Immune Responses

The ability to align individual cellular information from multiple experimental sources, techniques and systems is fundamental for a true systems-level understanding of biological processes. While single-cell transcriptomic studies have transformed our appreciation for the complexities and contributions of diverse cell types to disease, they can be limited in their ability to assess protein-level phenotypic information and beyond. Therefore, matching and integrating single-cell datasets which utilize robust protein measurements across multiple modalities is critical for a deeper understanding of cell states, and signaling pathways particularly within their native tissue context. Current available tools are mainly designed for single-cell transcriptomics matching and integration, and generally rely upon a large number of shared features across datasets for mutual Nearest Neighbor (mNN) matching. This approach is unsuitable when applied to single-cell proteomic datasets, due to the limited number of parameters simultaneously accessed, and lack of shared markers across these experiments. Here, we introduce a novel cell matching algorithm, Matching with pARtIal Overlap (MARIO), that takes into account both shared and distinct features, while consisting of vital filtering steps to avoid sub-optimal matching. MARIO accurately matches and integrates data from different single-cell proteomic and multi-modal methods, including spatial techniques, and has cross-species capabilities. MARIO robustly matched tissue macrophages identified from COVID-19 lung autopsies via CODEX imaging to macrophages recovered from COVID-19 bronchoalveolar lavage fluid via CITE-seq. This cross-platform integrative analysis enabled the identification of unique orchestrated immune responses within the lung of complement-expressing macrophages and their impact on the local tissue microenvironment. MARIO thus provides an analytical framework for unified analysis of single-cell data for a comprehensive understanding of the underlying biological system.

bioinformatics↗

bioRxiv2021

Virus-Dependent Immune Conditioning of Tissue Microenvironments

A thorough understanding of complex spatial host-disease interactions in situ is necessary in order to develop effective preventative measures and therapeutic strategies. Here, we developed Protein And Nucleic acid IN situ Imaging (PANINI) and coupled it with Multiplexed Ion Beam Imaging (MIBI) to sensitively and simultaneously quantify DNA, RNA, and protein levels within the microenvironments of tissue compartments. The PANINI-MIBI approach was used to measure over 30 parameters simultaneously across large sections of archival lymphoid tissues from non-human primates that were healthy or infected with simian immunodeficiency virus (SIV), a model that accurately recapitulates human immunodeficiency virus infection (HIV). This enabled multiplexed dissection of cellular phenotypes, functional markers, viral DNA integration events, and viral RNA transcripts as resulting from viral infection. The results demonstrated immune coordination from an unexpected upregulation of IL10 in B cells in response to SIV infection that correlated with macrophage M2 polarization, thus conditioning a potential immunosuppressive environment that allows for viral production. This multiplexed imaging strategy also allowed characterization of the coordinated microenvironment around latently or actively infected cells to provide mechanistic insights into the process of viral latency. The spatial multi-modal framework presented here is applicable to deciphering tissue responses in other infectious diseases and tumor biology.

immunology↗

bioRxiv2021

Integrated plasma proteomic and single-cell immune signaling network signatures demarcate mild, moderate, and severe COVID-19

The biological determinants of the wide spectrum of COVID-19 clinical manifestations are not fully understood. Here, over 1400 plasma proteins and 2600 single-cell immune features comprising cell phenotype, basal signaling activity, and signaling responses to inflammatory ligands were assessed in peripheral blood from patients with mild, moderate, and severe COVID-19, at the time of diagnosis. Using an integrated computational approach to analyze the combined plasma and single-cell proteomic data, we identified and independently validated a multivariate model classifying COVID-19 severity (multi-class AUCtraining = 0.799, p-value = 4.2e-6; multi-class AUCvalidation = 0.773, p-value = 7.7e-6). Features of this high-dimensional model recapitulated recent COVID-19 related observations of immune perturbations, and revealed novel biological signatures of severity, including the mobilization of elements of the renin-angiotensin system and primary hemostasis, as well as dysregulation of JAK/STAT, MAPK/mTOR, and NF-{kappa}B immune signaling networks. These results provide a set of early determinants of COVID-19 severity that may point to therapeutic targets for the prevention of COVID-19 progression. SummaryFeyaerts et al. demonstrate that an integrated analysis of plasma and single-cell proteomics differentiates COVID-19 severity and reveals severity-specific biological signatures associated with the dysregulation of the JAK/STAT, MAPK/mTOR, and NF-{kappa}B immune signaling networks and the mobilization of the renin-angiotensin and hemostasis systems.

immunology↗

bioRxiv2020

Single-cell profiling of Ebola virus infection in vivo reveals viral and host transcriptional dynamics

Ebola virus (EBOV) causes epidemics with high case fatality rates, yet remains understudied due to the challenge of experimentation in high-containment and outbreak settings. To better understand EBOV infection in vivo, we used single-cell transcriptomics and CyTOF-based single-cell protein quantification to characterize peripheral immune cell activity during EBOV infection in rhesus monkeys. We obtained 100,000 transcriptomes and 15,000,000 protein profiles, providing insight into pathogenesis. We find that immature, proliferative monocyte-lineage cells with reduced antigen presentation capacity replace conventional circulating monocyte subsets within days of infection, while lymphocytes upregulate apoptosis genes and decline in abundance. By quantifying viral RNA abundance in individual cells, we identify molecular determinants of tropism and examine temporal dynamics in viral and host gene expression. Within infected cells, we observe that EBOV down-regulates STAT1 mRNA and interferon signaling, and up-regulates putative pro-viral genes (e.g., DYNLL1 and HSPA5), nominating cellular pathways the virus manipulates for its replication. Overall, this study sheds light on EBOV tropism, replication dynamics, and elicited immune response, and provides a framework for characterizing interactions between hosts and emerging viruses in a maximum containment setting.

microbiology↗

bioRxiv2020

Integration of Mechanistic Immunological Knowledge into a Machine Learning Pipeline Increases Predictive Power

The dense network of interconnected cellular signaling responses quantifiable in peripheral immune cells provide a wealth of actionable immunological insights. While high-throughput single-cell profiling techniques, including polychromatic flow and mass cytometry, have matured to a point that enables detailed immune profiling of patients in numerous clinical settings, limited cohort size together with the high dimensionality of data increases the possibility of false positive discoveries and model overfitting. We introduce a machine learning platform, the immunological Elastic-Net (iEN), which incorporates immunological knowledge directly into the predictive models. Importantly, the algorithm maintains the exploratory nature of the high-dimensional dataset, allowing for the inclusion of immune features with strong predictive power even if not consistent with prior knowledge. In three independent studies our method demonstrates improved predictive power for clinically-relevant outcomes from mass cytometry data generated from whole blood, as well as a large simulated dataset.

bioinformatics↗

bioRxiv2019

Coordinated cellular neighborhoods orchestrate antitumoral immunity at the colorectal cancer invasive front

Antitumoral immunity requires organized, spatially nuanced interactions between components of the immune tumor microenvironment (iTME). Understanding this coordinated behavior in effective versus ineffective tumor control will advance immunotherapies. We optimized CO-Detection by indEXing (CODEX) for para ffin-em bedded tissue microarrays, enabling profiling of 140 tissue regions from 35 advanced-stage colorectal cancer (CRC) patients with 56 protein markers simultaneously. We identified nine conserved, distinct cellular neighborhoods (CNs)-a collection of components characteristic of the CRC iTME. Enrichment of PD-1+CD4+ T cells only within a granulocyte CN positively correlated with survival in a high-risk patient subset. Coupling of tumor and immune CNs, fragmentation of T cell and macrophage CNs, and disruption of inter-CN communication was associated with inferior outcomes. This study provides a framework for interrogating complex biological processes, such as antitumoral immunity, demonstrating an example of how tumors can disrupt imm une functionality through interference in the concerted action of cells and spatial domains.

immunology↗