Biology subjects

Bunis, D.

Publications and source records attributed to Bunis, D..

5 recordsLinked to original sources

bioRxiv2025

Differential Assembly of Mouse and Human Tumor Microenvironments

Mouse models are frequently used to develop treatments for human cancer. Yet, we lack a comprehensive understanding of the comparative organization of mouse and human tumor microenvironments (mu/huTMEs). Through immunoprofiling of commonly used mouse models, we found that the immune composition of most muTMEs resemble poorly infiltrated human tumors extensively biased toward high macrophages densities. Relatedly, we discover species-specific biases of chemokine expression networks, factors which drive TMEs assembly. Further, assessing coarse cellular networks, we find conserved correlations between some immune cell frequencies, while other relationships only appear conserved in the huTMEs matching muTME profiles. Despite this variable alignment, we define robust cell type-specific gene expression programs conserved in TMEs across species and cohorts and identify ones that are coordinated between cell populations in both species. Together, we isolate and offer methods to study the multiple areas of hazard and opportunities for using mice to model human cancer. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=192 HEIGHT=200 SRC="FIGDIR/small/661217v1_ufig1.gif" ALT="Figure 1"> View larger version (71K): org.highwire.dtl.DTLVardef@22bcf7org.highwire.dtl.DTLVardef@a410b7org.highwire.dtl.DTLVardef@1455eb5org.highwire.dtl.DTLVardef@14cc6f5_HPS_FORMAT_FIGEXP M_FIG C_FIG

immunology↗

bioRxiv2025

Searching for influencers among placental immune cells in preeclampsia.

Cells in maternal and fetal immune systems may communicate, leading to immune tolerance during pregnancy; however, this hypothesis remains controversial. Here, we profiled single-cell transcriptional signatures in placental layers comprising the maternal-fetal interface and deep placenta, then searched for genes associated with preeclampsia. To investigate the underlying principle of the failure of immune tolerance, we started by clarifying the systemic framework, comprising models of immune interaction frequency (IIF) and specific triggers (i.e., influencers) of tolerance (IT). We generated single-cell transcriptional profiles of normal term (Norms) and preeclampsia preterm (PePT) parturitions. Fetal and maternal cells are admixed across the placenta, for both Norms and PePTs, rejecting the IIF model of immune failure during pregnancy posed by excessive interactions between fetomaternal cells. Whereas placental layers are well mixed with maternal cells, we identified a conserved gradual immune transition of fetal T-cells in both PePT and Norm, disproving the IIF model. To search for influencers of PePT in the IT model, we established and validated a classification model for PePT and Norm immune cells, including T-cells, and then prioritized major contributors to the classifier model, which are highly enriched in ligands and receptors (p = 5.98e-5). Among the prioritized ligand receptors, SPP1 and CD44 are suggested as influencers of inflammation signatures and were experimentally validated by the exclusive colocalization of SPP1- and CD44-expressing cells in the PePT placentas. Different interleukin-4 and interferon-{psi} levels in the serum and urine of PePTs further support the contribution of SPP1 to associated pathways, including allograft rejection. Our findings provide insight into the influence of specific immune interactions between cells in the human placenta and their influencer-derived impact on PePT.

bioinformatics↗

bioRxiv2023

Cyclone: an accessible pipeline to analyze, evaluate and optimize multiparametric cytometry data

In the past decade, high-dimensional single cell technologies have revolutionized basic and translational immunology research and are now a key element of the toolbox used by scientists to study the immune system. However, analysis of the data generated by these approaches often requires clustering algorithms and dimensionality reduction representation which are computationally intense and difficult to evaluate and optimize. Here we present Cyclone, an analysis pipeline integrating dimensionality reduction, clustering, evaluation and optimization of clustering resolution, and downstream visualization tools facilitating the analysis of a wide range of cytometry data. We benchmarked and validated Cyclone on mass cytometry (CyTOF), full spectrum fluorescence-based cytometry, and multiplexed immunofluorescence (IF) in a variety of biological contexts, including infectious diseases and cancer. In each instance, Cyclone not only recapitulates gold standard immune cell identification, but also enables the unsupervised identification of lymphocytes and mononuclear phagocytes subsets that are associated with distinct biological features. Altogether, the Cyclone pipeline is a versatile and accessible pipeline for performing, optimizing, and evaluating clustering on variety of cytometry datasets which will further power immunology research and provide a scaffold for biological discovery.

immunology↗

bioRxiv2022

Homeostatic cytokines reciprocally modulate the emergence of prenatal effector PLZF+CD4+ T cells in humans

The development of human adaptive immunity progresses faster than previously appreciated, with the emergence of memory CD4+ T cells alongside regulatory T (Treg) cells by the second trimester of pregnancy. We previously identified a prenatal-specific subset of PLZF+ CD4+ T cells with heightened effector potential that accounted for most memory T cells in the developing intestine and accumulated in the cord blood of infants exposed to prenatal inflammatory pathologies. However, the signals that drive their tissue distribution and effector maturation are unknown. In this report, we define the transcriptional and functional heterogeneity of prenatal PLZF+ CD4+ T cells and identify compartmentalization of Th-like effector function across the small intestine (SI) and mesenteric lymph nodes (MLN). We find that IL-7, which is more abundant in the SI relative to the MLN, drives the preferential expansion of naive PLZF+ CD4+ T cells via JAK/STAT and MEK/ERK signaling. Exposure to IL-7 induces a subset of PLZF+ CD4+ T cells to acquire a memory-phenotype and rapid effector function, identifying the human analogue of memory-phenotype CD4+ T cells. Further, IL-7 modulates the differentiation of Th1- and Th17-like PLZF+ CD4+ T cells, and thus likely contributes to the anatomic compartmentalization of prenatal CD4+ T cell effector function.

immunology↗

bioRxiv2021

Whole-tissue deconvolution and scRNAseq analysis identify altered endometrial cellular compositions and functionality associated with endometriosis

The uterine lining (endometrium) exhibits a pro-inflammatory phenotype in women with endometriosis, resulting in pain, infertility, and poor pregnancy outcomes. The full complement of cell types contributing to this phenotype has yet to be identified, as most studies have focused on bulk tissue or select cell populations. Herein, through integrating whole-tissue deconvolution and single cell RNAseq, we comprehensively characterized immune and nonimmune cell types in endometrium of women with or without disease and their dynamic changes across the menstrual cycle. We designed metrics to evaluate specificity of deconvolution signatures that resulted in single cell identification of 13 novel signatures for immune cell subtypes in healthy endometrium. Guided by statistical metrics, we identified contributions of endometrial epithelial, endothelial, plasmacytoid dendritic cells, classical dendritic cells, monocytes, macrophages, and granulocytes to the endometrial pro-inflammatory phenotype, underscoring roles for nonimmune as well as immune cells to the dysfunctionality of this tissue. Teaser SentenceCell type deconvolution and single cell RNAseq analysis identify altered endometrial cellular compositions in women with endometriosis

bioinformatics↗