Biology subjects

Mair, F.

Publications and source records attributed to Mair, F..

9 recordsLinked to original sources

bioRxiv2025

Memory CD4 T cells orchestrate neoadjuvant-responsive niches in colorectal cancer liver metastases

Colorectal cancer frequently progresses to liver metastases (CRLM), a stage with limited treatment options and poor prognosis. Neoadjuvant chemotherapy is used to control tumor growth and enable resection, yet many patients fail to respond, and the mechanisms underlying this variability remain unclear. To identify determinants of treatment response, we profiled T cell states and their spatial organization in CRLM. We found that spatial arrangement and polarization of CD4 memory T cell networks determine treatment outcome. In responders, Th1-like CD4 memory T cells organized with effector-memory CD8 T cells and antigen-presenting cells (APCs) into therapy-responsive immune niches (TRINs) that support CD4-mediated APC licensing and local immune engagement. Non-responders lacked such immune architecture, exhibiting myeloid-rich regions dominated by circulating-like CD4 memory and regulatory T cells. CD4-driven TRINs thus emerge as key determinants of chemotherapy efficacy and provide a rationale for developing biomarkers and strategies that enhance CD4-APC-CD8 crosstalk within organized immune niches. Statement of significanceTh1-polarized CD4 memory T cells form therapy-responsive immune niches (TRINs) that orchestrate CD4, CD8, and APC function in colorectal cancer liver metastases, a clinically challenging and immunologically cold tumor type. TRINs define chemotherapy response and provide a mechanistic foundation for biomarker development and immunotherapy strategies designed to restore anti-tumor immunity.

immunology↗

bioRxiv2025

Measurement and prediction of unmixing-dependent spreading in spectral flow cytometry panels

Advances in spectral cytometry instrumentation and fluorescent reagents have led to the possibility of ultra-high-parameter panels exceeding 50 colors. However, panel size is limited in practice by unmixing-dependent spreading (UDS), a mathematical phenomenon which leads to a progressive deterioration of unmixed signal-to-noise ratios in panels that contain fluorochrome combinations with significant spectral overlap. Choosing spectrally compatible sets of fluorochromes that avoid UDS is a complex and labor-intensive task involving substantial trial-and-error experimentation. Here, we provide a detailed explanation of UDS and practical strategies for handling UDS in large spectral panels. We describe the empirical hallmarks of UDS, demonstrate how to quantify its impact, and dissect its underlying mathematical cause in terms of spectral collinearity. We present novel computational metrics that can be used to select optimal combinations of fluorochromes in a platform-agnostic fashion based on publicly available reference data, providing a general tool for spectral panel design.

bioinformatics↗

bioRxiv2024

Investigating Polyreactivity of CD4+ T Cells to the Intestinal Microbiota

The symbiotic relationship between host and microbiota plays a pivotal role in training and development of the hosts innate and adaptive immune systems. Antigen-specific recognition of microbiota by T cells enforces tolerance at homeostasis. Conversely, dysbiosis--characterized by alterations in microbiota diversity and abundance--leads to imbalanced T cell responses and triggering of inflammatory and autoimmune diseases. Despite their significance, the identities of immunogenic microbial antigens are still largely enigmatic. Here, we leveraged an in-house developed antigen screening platform, the MCR system 1, to delineate CD4+ T cell reactivity against Akkermansia muciniphila (AKK) and Bacteroides thetaiotaomicron (BT), --two prominent members of the gut microbiota. T-cell hybridomas reactive to AKK and BT bacteria showed polyreactivity to select microbiota-derived peptides in MCR co-cultures. We discovered 13 novel antigenic epitopes from AKK and 14 from BT. Steady-state T cells recognized these epitopes in an MHC-restricted fashion. Ex vivo stimulation of peptide-specific T cells revealed induction of type 1 and type 17 immune responses, albeit with non-overlapping specificities, contrary to MCR system results. Our findings further demonstrated that most identified epitopes are broadly conserved within the given phylum and originate from both membrane and intracellular proteins. Our work showcases the potential of the MCR system for identifying immunogenic microbial epitopes, providing a valuable resource. Additionally, it indicates the existence of mucosal T cells with a tropism toward broadly conserved bacterial epitopes. Overall, our study forms the basis for decoding antigen specificity in immune system-bacterial interactions, with applications in understanding both microbiome and pathogenic bacterial immunity.

immunology↗

bioRxiv2024

Converging cytokine and metabolite networks shape asymmetric T cell fate at the term human maternal-fetal interface

Placentation presents immune conflict between mother and fetus, yet in normal pregnancy maternal immunity against infection is maintained without expense to fetal tolerance. This is believed to result from adaptations at the maternal-fetal interface (MFI) which affect T cell programming, but the identities (i.e., memory subsets and antigenic specificities) of T cells and the signals that mediate T cell fates and functions at the MFI remain poorly understood. We found intact recruitment programs as well as pro-inflammatory cytokine networks that can act on maternal T cells in an antigen-independent manner. These inflammatory signals elicit T cell expression of co-stimulatory receptors necessary for tissue retention, which can be engaged by local macrophages. Although pro-inflammatory molecules elicit T cell effector functions, we show that additional cytokine (TGF-{beta}1) and metabolite (kynurenine) networks may converge to tune T cell function to those of sentinels. Together, we demonstrate an additional facet of fetal tolerance, wherein T cells are broadly recruited and restrained in an antigen-independent, cytokine/metabolite-dependent manner. These mechanisms provide insight into antigen-nonspecific T cell regulation, especially in tissue microenvironments where they are enriched.

immunology↗

bioRxiv2023

50-color phenotyping of the human immune system with in-depth assessment of T cells and dendritic cells

We report the development of an optimized 50-color spectral flow cytometry panel designed for the in-depth analysis of the immune system in human blood and tissues, with the goal of maximizing the amount of information that can be collected using currently available flow cytometry platforms. We established and tested this panel using peripheral blood mononuclear cells (PBMCs), but included CD45 to enable its use for the analysis of human tissue samples. The panel contains lineage markers for all major immune cell subsets, and an extensive set of phenotyping markers focused on the activation and differentiation status of the T cell and dendritic cell (DC) compartment. We outline the biological insight that can be gained from the simultaneous measurement of such a large number of proteins and propose that this approach provides a unique opportunity for the comprehensive exploration of the immune status in tissue biopsies and other human samples with a limited number of cells. Of note, we tested the panel to be compatible with cell sorting for further downstream applications. Furthermore, to facilitate the wide-spread implementation of such a panel across different cohorts and samples, we established a trimmed-down 45-color version which can be used with different spectral cytometry platforms. Finally, to generate this panel, we utilized not only existing panel design guidelines, but also developed new metrics to systematically identify the optimal combination of 50 fluorochromes and evaluate fluorochrome-specific resolution in the context of a 50-color unmixing matrix.

immunology↗

bioRxiv2021

Convergent clonal selection of donor- and recipient-derived CMV-specific T cells in hematopoietic stem cell transplant patients

Competition between antigen-specific T cells for peptide:MHC (p:MHC) complexes shapes the ensuing T cell response. Mouse model studies provided compelling evidence that competition is a highly effective mechanism controlling the activation of naive T cells. However, assessing the effect of T cell competition in the context of a human infection requires defined pathogen kinetics and trackable naive and memory T cell populations of defined specificity. A unique cohort of non-myeloablative hematopoietic stem cell transplant (nmHSCT) patients allowed us to assess T cell competition in response to CMV reactivation, which was documented with detailed virology data. In our cohort, HSCT donors and recipients were CMV-seronegative and -positive, respectively, thus providing genetically distinct memory and naive T cell populations. We used single-cell transcriptomics to track donor versus recipient-derived T cell clones over the course of 90 days. We found that donor-derived T cell clones proliferated and expanded substantially following CMV-reactivation. However, for immunodominant CMV epitopes, recipient-derived memory T cells remained the overall dominant population. This dominance was maintained despite more robust clonal expansion of donor-derived T cells in response to CMV reactivation. Interestingly, the donor-derived T cells that were recruited into these immunodominant memory populations shared strikingly similar TCR properties with the recipient-derived memory T cells. This selective recruitment of identical and nearly identical clones from the naive into the immunodominant memory T cell pool suggests that competition does not interfere with rejuvenating a memory T cell population, but results in selection of convergent clones to the memory T cell pool. SignificanceAn existing memory T cell population specific for a single epitope is sufficient to effectively curtail responses to any new antigens if the original epitope is present in a vaccination regimen or heterologous infections. We asked if T cell competition precludes recruitment of any new, naive T cells to an existing memory T cell pool in context of CMV-specific T cell responses in a cohort of transplant patients. Our data indicate that competition does not prevent recruitment of naive T cells into the memory T cell pool, but selects for T cells with nearly or fully congruent T cell receptor specificities. We discuss the implications of rejuvenating a memory T cell pool while preserving the T cell receptor repertoire.

immunology↗

bioRxiv2021

Superscan: Supervised Single-Cell Annotation

Automated cell type annotation of single-cell RNA-seq data has the potential to significantly improve and streamline single cell data analysis, facilitating comparisons and meta-analyses. However, many of the current state-of-the-art techniques suffer from limitations, such as reliance on a single reference dataset or marker gene set, or excessive run times for large datasets. Acquiring high-quality labeled data to use as a reference can be challenging. With CITE-seq, surface protein expression of cells can be directly measured in addition to the RNA expression, facilitating cell type annotation. Here, we compiled and annotated a collection of 16 publicly available CITE-seq datasets. This data was then used as training data to develop Superscan, a supervised machine learning-based prediction model. Using our 16 reference datasets, we benchmarked Superscan and showed that it performs better in terms of both accuracy and speed when compared to other state-of-the-art cell annotation methods. Superscan is pre-trained on a collection of primarily PBMC immune datasets; however, additional data and cell types can be easily added to the training data for further improvement. Finally, we used Superscan to reanalyze a previously published dataset, demonstrating its applicability even when the dataset includes cell types that are missing from the training set.

bioinformatics↗

bioRxiv2019

Progressive differentiation of memory CD8 T cells in the cervicovaginal tissue

Tissue-resident memory CD8 T cells (CD8 TRM) are critical for maintaining barrier immunity. CD8 TRM have been mainly studied in the skin and gut with recent studies suggesting that the signals that control tissue-residence and phenotype are highly tissue-dependent. We examined the T cell compartment in healthy human cervicovaginal tissue (CVT) and found that most CD8 T cells were granzyme B+ and TCF-1-. To address if this phenotype is driven by CVT tissue-residence, we used a mouse model to control for environmental factors. Using localized and systemic infection models, we found that CD8 TRM in the mouse CVT gradually acquired a granzyme B+, TCF-1- phenotype as seen in human CVT. In contrast to CD8 TRM in the gut, these CD8 TRM were not stably maintained regardless of the initial infection route, which led to reductions in local immunity. Our data show that residence in the CVT is sufficient to progressively shape the size and function of its CD8 TRM compartment. SummaryThe tissue-resident memory (TRM) CD8 T cell compartment in human and mouse cervicovaginal tissue (CVT) is remarkably similar. The CVT TRM compartment is maintained autonomously and does not reach phenoypical or numerical equilibrium. The numerical decline leads to impaired viral control in a secondary challenge.

immunology↗

bioRxiv2019

A targeted multi-omic analysis approach measures protein expression and low abundance transcripts on the single cell level

High throughput single-cell RNA sequencing (sc-RNAseq) has become a frequently used tool to assess immune cell function and heterogeneity. Recently, the combined measurement of RNA and protein expression by sequencing was developed, which is commonly known as CITE-Seq. Acquisition of protein expression data along with transcriptome data resolves some of the limitations inherent to only assessing transcript, but also nearly doubles the sequencing read depth required per single cell. Furthermore, there is still a paucity of analysis tools to visualize combined transcript-protein datasets.\n\nHere, we describe a novel targeted transcriptomics approach that combines analysis of over 400 genes with simultaneous measurement of over 40 proteins on more than 25,000 cells. This targeted approach requires only about 1/10 of the read depth compared to a whole transcriptome approach while retaining high sensitivity for low abundance transcripts. To analyze these multi-omic transcript-protein datasets, we adapted One-SENSE for intuitive visualization of the relationship of proteins and transcripts on a single-cell level.

immunology↗